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North

Carofina

9tme

Library

Raleigh

^4.

c

DOC.

Review

and

Evaluation of

Oil

Spill Models

for

Application

to

North

Carolina

Waters

M

2

im

Bruce

J.

Muga

Consulting Engineer

Durham,

NC

AUGUST 1982

North

Carolina

Coastal

Energy

Impact Program

Office of Coastal

Management

North Carolina

Department

of Natural Resources

and Community

Development

CEIP

REPORT

NO.

31



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contact:

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Energy Impact Program

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Coastal Management

N.C. Department

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Development

Box

27687

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27611

Series

Edited by James F. Smith

Cover

Design by Jill Miller



REVIEW AND EVALUATION OF OIL

SPILL

MODELS

(for Application to

North

Carolina Waters)

by

Bruce

J.

Muga

Consulting Engineer

Durham,

North

Carolina

Prepared

for

Office of

Natural

Resources Planning and Assessment

N.

C.

Department

of Natural

Resources

and

Community Development

The preparation

of this

report

was funded by

a

Coastal

Energy

Impact

Program grant from

the

North

Carolina Coastal Management

Program,

through

funds provided

by the Coastal Zone Management

Act of

1972,

as amended, which

is

administered

by the

Office

of

Coastal Zone Management, National

Oceanic

and

Atmospheric

Administration.

The

CEIP

grant

was

part

of

NOAA

grant

NA-79-AA-D-CZ097.

August

1982

CEIP

Report No.

31



Digitized

by

the Internet

Archive

in

2011 with

funding

from

State

Library

of

North

Carolina

http://www.archive.org/details/reviewevaluationOOmuga



Acknowledgements

This

study

was

funded

by

a

grant from the

Coastal Energy

Impact

Program

(CEIP), Department of

Natural

Resources and Community Development

(DNRCD)

.

In

particular,

the

author

wishes to

acknowledge the

efforts of

Mr. Jim

Sm.ith

, CEIP Coordinator,

Office of

Coastal

Management,

DNRCD,

and

Mr. Roger Schecter,

Chief,

Permit

Information

and

Assistance

Section, Office

of

Planning

and Assessment, DNRCD.

Mr.

Smith arranged

for

this

particular study

to

be

undertaken following

completion of

the objectives of an earlier

study

under

the

original

grant.

Mr.

Schecter served as

Contract

Monitor

and

was

very

helpful

in

securing certain

references.

The

author

also

wishes

to

acknowledge

the

help

of

Mr.

Eric

Vernon,

Office of

Marine Sciences,

Department

of

Administration, who

provided

some

important

but difficult

to

obtain

references.

Finally, the

author

appreciates the

help

of

Ms.

Anne

Taylor,

Director

of the Office

of

Planning

and

Assessment,

DNRCD.

Ms.

Taylor completed

all

of

the

necessary but

burdensome

paperwork

to

ensure

availability

of

funds

for the

original

grant

objectives.

The

encouragement, help, patience and

under-

standing

of

all of

the

aforementioned

personnel is

greatly

appreciated.



CONTENTS

Chapter

Page

1

Introduction

,

,

. .

1

2 Background

4

Problem

Formulation

7

Spreading

and

Dispersion

Model Solution

,

11

3

Review

of Literature

17

Advection

18

Wind

20

Surface Currents

23

Subsurface Currents

25

River

Currents

25

Waves

26

Spreading and

Dispersion

26

Evaporation

32

4

Evaluation of Oil Spill

Models

for Use

in

North Carolina

Waters

....

35

Inland

Waters

and

Estuaries

44

Nearshore

46

Offshore

49

5

Summary

and

Conclusions

54

Recommendations

56

References

59

Appendix

60



List

of

Tables

Table

Page

I

Processes

of

Importance

to

the

Oil Spill

and

Transport Problem

....

6

II

Spreading

Laws

for

Various

Regimes

According

to

Fay

(1971)

12

III

Oil Spill

Models

19

IV

Wind Field

Model

Types

21

V

Types

of

Spreading Models

28

VI

Classification

of

Evaporation

Submodels

33

VII

Candidate Models for

Application

to

North

Carolina

Waters

43

List of

Figures

Figure

Page

1

Time-Length Scale Diagram

for

Determination of

Relative

Importance of

Various Processes

.... 15

2

Time-Length Scale

Diagram

for

Evaluating

Relative Importance

of Various

Processes

38



Chapter

1

Introduction

Recent

interest in

exploratory

drilling

for

hydrocarbon

deposits off

the

coastlines of

North Carolina

and

neighboring states has disclosed

the

need

to

under-

stand

a

number

of environmental risks attendant

to

this

activity. Among

the

most

important

of

these risks is the

spillage

of

liquid hydrocarbons.

Since risk

is

the

product

of the probability

of

occurrence

of

an event

and

its effect

(should the event

occur),

the transport

mechanisms of spills

is

a

topic of

critical

interest.

This

topic

has

been

the

object

of numerous

studies in recent

years.

These

studies have

resulted

in

the

development

of

various models

for

predicting

the

movement

of spills.

Each

of

these

models

was

developed

for

a

particular

set of

conditions. The

result is that

no reliable

prediction

scheme

has

yet evolved

which is

applicable

to

a general

set

of conditions.

It is note-

worthy

to

mention

that

develocment of

such

a

scheme

is

a

formidable

task.

Therefore,

the

main focus of

this study

is an

evaluation

of

the

methods for predicting

the

movement

of

oil

spills under the

particular

environmental

conditions that exist in

North

Carolina waters.

Although



the

idea

for

this

study

stems

from

the

potential

drilling

activity

offshore,

our

interest

in

models for

predicting

spill movements is

not

limited

to

these

occurrences.

To

a

parallel

degree,

we are

interested in

methods

for

predicting spills that

occur

in connection with

the

transportation

and transfer

of

hydrocarbons within

and

adjacent

to

North

Carolina waters. For example,

methods

for

predicting

the

movement

of

spills

that occur in ports,

harbors

and/or estuaries

as well as along

the

adjacent

transportation

routes

of North

Carolina,

are

also

of

concern

.

In

response to

the

various

needs,

oil

spill

models have

evolved

along two separate

paths.

The earliest

models

were

developed

to

predict

one-of-a-kind

events

occurring in

real

time.

These

are after-the-fact

models

and

depend upon reliable

wind

and

current forecasts

for

achieving

even moderate

success.

Most

frequently, these

models

were

roughly

calibrated

from

real observations

taken

during

and

following

a

spill.

Such

models, of

necessity,

are

program.med to accept

real time

data

as

input.

With

the passage of

time,

other

model

types were

developed

in connection with the evaluation

of

various

impacts. These

models

are

much

more

sophisticated

than

the

earlier models and

are

designed

to

assist

decision

makers in

the

environmental

assessment

and

planning



processes.

These

models

use

the

historical climatological

data

as input and

are programmed

to

generate

sufficient

data to

disclose all possible consequences

of an

event.

For

other fundamental

reasons,

the former and

latter

models tendea

to be

deterministic

and

probabalistic

in

nature,

respectively.

This

characteristic

will

be

examined in

more

detail in the following section.

Bishop

(1979)

has categorized the model types according

to

Type I,

Type

II

or

Type III,

which he

describes

as

follows:

Type I models;

Multiple

trajectory models

for

long-term

strategic forecasts

based on

archived

data.

Type II

models: Single event

(highly

structural)

models for

specific

day-to-day

tactical

forecasts

usually

based on

up-to-date

data,

and

Type

III

models:

Type

I

or

Type

II models

implemented in

a receptor

(reverse)

mode

such

that one

can

project

areas

from which

trajectories

would impact

resources.

We

see that Type

III models

are

not

really

a

separate

category

but

rather

a

unique

application

and

use

of

either Type I

or

Type

II

models.

It is

also

interesting

to

observe that

the sequence

of

presentation

is actually

the

reverse

of the

historical development.

In

other words,

Type

II

models

evolved and preceeded

the

development

of

Type

I

models.



Chapter

2

Background

There

is a

substantial

volume of

literature

dealing

with

oil spills,

most

of

it

of recent

origin.

Surprisingly,

there

have been

only a few attempts

to

review

the

literature

in

a

systematic manner within

a

comprehensive

framework

of

the overall

problem.

The

work

by Stolzenbach,

et

.

al

.

(1977)

is an

important

reference

in this regard. Most

of the

studies

as

published in the

open

literature

treat only

one

aspect

of the

overall

problem in an isolated context

and

often

under

a

narrow

combination

of

circumstances that make it

difficult

to apply the

results

to

other situations

with

reasonable confidence.

It is instructive

to

make a

few

preliminary

observations

in

connection

with

the treatment of the

oil

spill problem.

This is

a

general

problem

in

the

field

of

fluid mechanics,

the

solution

for

which requires

a

broad understanding of

chemical

and biological processes

The

solution can be

approached

in

one of

two

fundamental

ways;

i.e.,

probabalistic or

deterministic.

Because of the fact

that

(1)

the

environment

(i.e.,

winds,

waves

and

currents)

has an

enormous

influence

on

the

spill

behavior,

and

(2)

the

environment

4



is

a

geophysical random process,

one would

expect

that

the approach should be

a

probabalistic one.

In

other

words,

the solution approach should

be

compatible

with

the

nature

of

the

problem. On

the other hand,

there

are

some

features

of

the

problem

which

are

decidedly

deter-

ministic.

An

example would

be the sprea.ding

of oil

on

a

quiescent sheltered

body

of water

in

the absence of

any

winds,

waves

or currents.

Also,

the

approaches

are

not

mutually exclusive since elements of deterministic methods

can

be

and

are incorporated

within probabalistic-based

approaches

and

vice-versa. In reviewing the

literature,

it

is

important to

recognize the existence of these two

fundamental solution methods.

In

view of

the realization

that

the

probabalistic

nature of the

problem

derives

from

consideration

of the

environmental

influences

(which

have

regional

'geographic'

dependency) and that

the deterministic

influence is

based

on

the physical

mechanics

of

the problem, we

can

identify

two

broad

categories of processes which are

of

importance

to

the oil

spill

and transport

problem.

These

processes

are depicted in

Table

I

,

with

some

explanatory

notation

.

The

spreading

and

dispersion

processes are,

to

a large

degree,

geographic-independent,

but are,

neverthe-

less,

dependent

upon certain

characteristics

of

the

event



TABLE

I

Processes

of

Importance

to

the

Oil

Spill

and

Transport

Problem

Process

Nature

Dependency

Spreading

Deterministic

Oil properties

at ambient

temperature, largely site

dependent

Dispersion Deterministic

(with

probabalistic

elements)

Turbulence intensities in

water medium,

weakly site

dependent

Advection (Drift)

(wind,

currents, waves)

Probabalistic

(with

deterministic

elements)

Strength of

advecting

fluids, strongly site

dependent

Weathering

and Other

Processes

biodegradation

dissolution

emulsif

ication

evaporation

oxidation (photo)

patch (large-size)

breakup

sinking

and

sedimentation

Probabalistic

and

Deterministic

Various

site dependent

and

site

independent

conditions



such

as

spill

size,

rate

of

spill

and

other

physical

and

chemical

characteristics which describe the

spill

material

and

receiving

waters.

In

contrast,

the advection

(drift),

weathering and

other

processes are

directly

related to

and

dependent

upon

conditions

that

characterize the site

environment

at the time of the spill

and

immediately

thereafter. In other

words,

the processes which characterize

oil

spill

movement consist

of both

site-dependent

and

site-independent

ones. A brief

review

of

the various

processes governing

the

mechanics of

the problem is

presented in

the following

section.

Problem

Formulation. Stolzenbach, et.al.(1977)

have

formulated

the

essential boundary

value

problem

for

oil

slick transformations. The

system

of

differential

equations

were

derived on the basis of some

simplifying

assumptions and

averaging

approximations.

The simplifying

assumptions

seem

to

be well

justified and

are

used to

some degree in

all

of the

models

that have been

developed

and

reported in the

literature. Therefore,

any

error due

to

the

simplifying

assumptions

would

not

affect

any

relative

evaluation

of the

various

models.

With regard

to

the averaging

approximations,

Stolzenbach,

et.al.

(1977)

states

that

it is

justified only

for the

analysis

of the

oil motion

and may

not

be

a

good approximation

for studying

the diffusion

of

oil through

the

slick

boundaries.



The

continuity

equation

which

expresses

the

conservation of mass

relationship

appears

as

9c.

h

3uhc

.

9vhc

.

„

„—

„

.—

^J-

+ -^+-^=

k.

[/

(h|^)

+^

(h|^)]

-4,

.

-d,^.

-

R.h

(1)

9t

3x

9y

1

9x

9x

9y

9y

si

bi i

The conservation

of momentum relationship

appears

as

9u

,

—

9u

,

~

9u

,

w

^

^

9h

bx

,

sx

,^^

^

^

^

^

^

97

= ^

^T~^

9^

-

^

^

^

(2a)

9v

,

—

9v

,

—

9u /__w_.

9h

by

,

sy

,„, ^

The

boundary

condition

on

the

slick boundary

appears

as

f=a-a-a

(3)

n

aw oa

ow

In

the

above equations,

x,y

=

variables

of

moving

coordinate

system

with

respect

to origin

at

center of

mass of oil

slick

u,v

=

components of

oil

particle

velocities

relative

to

the

center

of mass

of the

slick

C.

=

mass

per

unit

volume of

oil of

the

ith oil

fraction



h

=

local slick

thickness

k.

=

molecular

diffusion

rate for

ith

oil

fraction

within the slick

R.

=

rate

of

removal

of

the

ith

oil

fraction

per

unit

volume

d)

.

=

flux

of

the ith

oil fraction

outward

si

through

the

surface

of

the slick

4),

.

=

flux

of the

ith

oil fraction

outward

through

the

bottom of the

slick

p

=

average density of

oil

mass

within

the slick

p

=

density of water underlying the oil

slick

t

=

time

T ,T

=

shear

stresses

on oil

slick

surface

sx '

sy

T, ,T,

=

shear

stresses

on oil

slick

bottom

bx

'

by

g

=

acceleration

due

to

gravity

f

=

net

surface tension

per

unit length

of

oil slick

boundary

a

,a

,0

=

surface

tension

of air-water,

air-oil

aw'

oa

ow

j

-n ^ ^

^

-^

^

and oil water interfaces, respectively

Equations

(1)

through

(3)

constitute,

in

a

simplified form,

the boundary value

problem of

oil

slick

transformations. In

relating the

physical

processes

shown

in

Table

1 tc

the

various

terms

in the

system

of

equations,

we

can

point

out

that

the

effects

of

weathering

(and

other

processes) are

treated

indirectly

via

the

concentration

term

C.

for the different

oil components

and

directly

by

the

last

three terms of

Equation

(1).

9



We

can

also

note that

the

motions

(i.e., particle

velocities

u

and

v)

are

given relative

to the center

of

mass

of

oil

in

the

slick. Therefore,

motions resulting

from

the advection

processes

(appropriate

for the center 6f

mass

of

the slick)

must

be

superposed

on the

relative

velocities

to

determine

the

motions

in

an absolute

sense.

In

a

preliminary

review

o:*

the literature, we

found

that

models

for

the

spreading,

dispersion and

advection

processes

have been

developed

and

compared

with

model and prototype

data

to

a

sufficient

degree

to

enable

some reasonable conclusions

and

evaluations

to

be

made.

Except

for

evaporation,

this

is not

the

case

for

other

weathering

processes

which

remain

incompletely

understood.

Moreover,

the

interactions between

weather-

ing

and

the other processes

is

even more

poorly

understood.

As a

consequence,

the

scope

of

this

study

is

limited

to

an assessment of

the

spreading, dispersion

and advection

models

and

their

applicability

to

North Carolina

waters.

In addition, some comments

concerning evaporation

models

and

models of other weathering processes

will

be

provided

but

it

is

beyond the

scope

of the

present

study

to

consider

such

models

on

the

same

level

with spreading,

dispersion

and

advection

models,

10



Spreading

and

Dispersion

Model

Solutions.

Returning

to

the

fundamental

system of equations,

different

solutions

can

be

obtained depending on the

type of

additional

simplifications

that

can

be made. As indicated by

Stolzenbach,

et

.

al

.

(1977)

two broad

categories

of

solutions

can

be identified. These

are

the spreading and

dispersion

solutions. The

distinction

between these

two

processes

(and

solutions) depends upon

the

relative

strength

of

the

external

shear stresses acting on the

oil

slick.

If the

external shear

forces

(i.e.,

the

last

two

terms

of

Equations

(2))

are

absent, or negligible,

then the

solution

corresponds

to

the

spreading

process

since

the

resulting

motion

depends

upon

the

density

differences

and

inter-

facial tensions.

On

the

other

hand,

if the

external

shear

forces

are

very large, then the

solution

corresponds

to

the dispersion

process.

Most,

if

not

all, of

the

spreading

solutions

appear to be

based

on or related in some way to

the work

of

Fay

(1969,

1971). Two sets of results

have

been

obtained

which

are

based on certain

idealistic

assumptions.

The

one-dimensional

set

of results is

appropriate

when

it

is

assumed

that

the

slick

spreads

in one

direction

only.

The

two-dimensional

case is based on

radial

spreading.

A

summary

of

the spreading

functions

for

the two

different

sets of results is given in Table II.

These

functions

11



TABLE II

Spreading Laws

for

Various

Regimes

According

to

Fay

(1971)

Regime

(Driving/Resisting Force)

Spreading

Formula

One-Dimensional

Radial

Gravitational/Inertial

L

=

k„

D

=

2k

rP

-P

iL

w

Gravitational/

Viscous

L

=

k.

p.rp

-

1

(-^)AtVv^

w

H

D

=

2k

•

P

-p

2

T

(-J^)

V^t

/v^

Surface

Tension/Viscous

L

=

k„

ia^tVp

2

V

X.3

|_

W

D

=

2k

3

I

a^tVp'v

w

w

here

P

P

g

D

A

V

V

a

t

=

density of water

=

density

of oil

=

acceleration

of

gravity

=

length

of

one-dimensional

oil

spill from

fixed

origin

to leading

edge of

oil

slick solubility

=

diameter of radial

(axisymmetric)

spill

=

volume of oil

per unit

length

normal

to

spill

direction

=

volume

of

oil

=

kinematic

viscosity of water

=

interfacial

tension

=

elapsed time

from

initial

spill

From various

sources,

the

coefficients

k

may have the following

values:

kij

=

1.33

k--

=

1.14

_/0.98 l

^r,

-Sl.l2(

I1.45J

k^

=1.60

12



are

presented with

the

unknown

length

(distance

from

leading edge to

center

of

gravity

of spill)

in an

explicit

formulation. The

other

known

or

assumed

variables

appear on

the

right-hand

side (RHS)

of the

equation

.

The

dispersion

models result in

the

following

solution

form:

i

12 2

jn

^^^

I

^

y

X

y

X

where

h

=

average spill thickness

m

=

total slick

mass

p

=

density

of

oil

and

a

and

a

are

related to the

dispersion coefficients,

X

y

respectively,

as

follows

9a

2

3a

^

^

=

2k

and

—

^—

=

2k

at

X

9t y

As noted

by

Stolzenbach,

et

.

al .

(1977)

observations

of real

oil

slicks rarely fit the

assumptions

made

in

formulating the

spreading

/dispersion models.

Thus, compari-

sons

between

observations

and

predictions

tend to

be

mixed.

As

a

result of this

behavior,

Stolzenbach, et

.

al

.

(1977)

13



conclude

that

1.

Both

spreading

and

dispersion

processes

may be important

in determining

the

total

growth

of the slick,

2.

Existing

techniques

for

estimating

the

growth

of

surface

oil

slicks

provide at

best only

an order of

magnitude estimate

of what

the

actual slick size will

be.

3.

Because

of

the

complex

and

usually random

nature

of

the

processes

controlling

slick

growth, it

is unlikely that

a

significant

improvement

in deterministic capability

will

be possible.

However,

estimates

of

the

variance in

slick

sizes should

become

more

accurate

as

additional

observations

are

obtained.

4. The

applicability

of

available

spreading

and dispersion models

should be

judged

on

a case by

case

basis in terms of

the

site specific conditions.

The

usefulness

of the

modeling

work as

well as

Stolzenbach

'

s

, et

.

al .

(1977)

review

lies

in

their develop-

ment

of

a

time

and

length

scale diagram, as

shown in

Figure

1

. Such

a

diagram

enables

one

to

determine

the

relative

importance of

the various

processes

which

affect

14



CO

•^

0)

tfl

o

<u

CO

e

/

^

.-H

CO

a;

•H

o •U

C

CO

QJ

•H

cu

CO

o

t

•H CO

/^

o

1

4-1

CO

iH

1

Cfl

ai

CJ 0)

1

c

o

r—

>

0)

i

1

•H

e

V4

P-.

o

>

1

(U

a>

•H

1

4-1

CO

-^

CO

J-)

1

Q)

3

r^

/^

O

1

Q

O

r^

f

e

0)

/

•H

CTn

o

>

/

-i

^ .H

o

I

—

TJ

/

O

CO

<

/

M-i

>

'

/

CO

a

CO

/

c

e

m

.-H

i

o

(0 CO

1

•H

-i

/

u

4-1

Cfl

CO

CD

4J

O

0)

/

<u

e

3

•H

C

I—

/

X.

cu

4-1

Q

CO

*^

/

u

4-1

o

4J

^

/

CO CO

3

0)

-(

O

/

(U

>,^

i-H

O

CO

iL

S

CO

f^

CO

O

N

J=

0)

I—

4-1

>

M

•H

4-1

C

4-1

C/^

0) CO

I

tH

1-1

0)

Pi

4-1

e

U-l

•H

iw

<;

H

O^-'

1-1

W

PS

t3

o

M'

O

O

15



oil spill

motions.

This diagram

clearly shows that

spreading

is important during the

early

stages

(or,

alternatively,

over

shorter distances)

of

a

spill

whereas

the

opposite

is

true

of

dispersion.

Other

processes

are

also

indicated.

An

example of

the use

of

such

a

diagram

in

the

case

of

selecting appropriate

models

for

North

Carolina

waters will be indicated

in

Chapter

4.

16



Chapter

3

Review

of Literature

As

noted

in the

introduction,

there has

been

an

enormous

volume

of literature

published within

recent

years on the subject

of

oil

spills. Approximately

200

references

constituting

roughly

15% of the available

number

of

articles

have

been

consulted

in connection

with

this

report.

Only

a

small

number

of

these

references

are cited

in the

bibliography, however,

since many

references

deal with

the topic

in only

a

peripheral

way.

From

these references,

about

2 5

distinct

modeling

efforts

have been

identified.

For

each

of these

efforts,

a

summary

report has

been

prepared identified

by

the

model name and

citing

the

primary reference

and

accompanying

abstract

along with

the

reviewers

comments.

These summary

reports,

one

for each modeling

effort are

presented in the

Appendix.

In this

section,

a

summary

of

the

reviews is presented

so

that

the reader can

gain

a

panoramic

view

of the

current

status

of

oil

spill models, To

reiterate, our

main

emphasis

is

concerned with

advection, spreading,

and

dispersion

processes and

with

evaporation.

For reasons

discussed

in

the

introduction,

less

emphasis

is

placed

on

other

weathering

processes.

Also,

we

are

concerned

with

application

of these

models to

North

Carolina

waters.

17



For that reason,

a number

of

Canadian

sources

were

not

consulted since, in

many

cases, they

deal with

Artie

conditions.

A

satisfactory means

of

classifying models

is

to take note of

the

processes that

the

model

considers.

This

has

been done

by Stolzenbach,

et

.

al

.

(1977)

and

is

presented herein

as

an update in Table III.

Discussions

are

presented in

the

following

paragraphs

for each of

the

major processes

that

are

of interest

to

this

study.

Advection.

Advection is probably

the

most

important

process by

which

oil spills are

transported

over any sensible

distance,

and is treated by

every oil

spill model

that

was

reviewed.

Advection

occurs

as

a

result

of wind and

currents

and to

an

unknown

extent

,

waves.

Both wind and

currents induce

shearing

stresses

on

the

top

and bottom surfaces,

respectively,

of

the oil

slick.

These

shearing

stresses,

in

turn,

cause

the oil

slick

to

move. Because of

the fact

that the

shearing

stresses are

not,

in general,

uniform

(or constant),

the

oil slick

experiences not only

a

net

motion of

its

center

of

mass

but

also

differential motions of the

oil slick

geometry

about

its

center

of mass. As a

matter of

fact,

the

shearing stresses

are,

in

the

general

case, time

and

space

dependent

18



TABLE

III

OIL SPILL

MODELS

(Listed

According to

Date of

Origination)

Processes Modeled

Advection

Advection

Advection

Advection

Advection

Advection

Advection

Model Name Date

1.

U.S. Navy

1970

2.

WGD 1972

3.

Narragansett

Bay

1973

4.

Tetra

Tech

,

Inc.

1974

5.

CEQ

1974

6.

BOSTM

1975

7. USCG

(New

York

Bight)

1975

8.

Delaware

Bay 1976

9.

USCG

(New York

Harbor)

10.

use/API

1977

11.

SLIKTRAK

(SLIKFORCAST,

OILSIM)

1977

12.

MOST

1978

13. DPPO (Garver

and Williams)

1978

14.

URI

(Georges

Bank)

1979

15. Puget

Sound 1979

16. CAES

1979

17.

Riverspill

1979

18. NWS/NOAA

1979

19.

USCG

(Long

Island

Sound)

1980

20.

SPILSIM

1980

21. EDIS

1980

22.

PIC

1980

23.

OSTA

1980

24. OSSM

1980

25.

DRIFT

1980

Spreading

Spreading,

Dispersion

Spreading,

Dispersion

Dispersion

Advection,

Spreading, Dispersion

Advection,

Spreading, Dispersion

Advection, Spreading, Dispersion,

Evaporation

Advection, Spreading,

Dispersion,

Evaporation

Advection,

Spreading,

Dispersion

Advection,

Spreading,

Dispersion,

Evaporation

Advection,

Spreading,

Dispersion,

Evaporation

Advection,

Spreading

Advection,

Spreading,

Dispersion,

Evaporation

Advection,

Spreading

Advection,

Spreading

Advection, Spreading,

Dispersion

Advection

Advection

Advection

Advection

Advection

Advection

Spreading

Spreading,

Dispersion

Spreading,

Dispersion

Spreading,

Dispersion,

Evaporation

Weathering

processes other than evaporation

are not listed.

19



Wind

.

A

substantial

effort

has

been

devoted

to

the

development

of wind

field

and

current

submodels.

One

of the distinguishing

features

of

oil

spill

models is

the

degree

of

realism

that has

been incorporated

into

their

wind and current

submodels.

In the

case

of

wind

models, this

degree ranges from

the

simplest

and crudest

approach

to

the

most elegant

and

sophisticated.

At

least

three

different

categories

can be

identified.

These

include constant

wind fields,

time

and

spatially dependent

wind

fields.

Table IV

is a

listing

of the

types

of wind

field

input

that

is programmed

for

oil

spill models that

were

reviewed.

A

majority of the

models can be

operated to

accept

either

measured

(or

real

time

data)

or

simulated

data.

The measured

data

is, in general,

time

and spatially

dependent

but this

may not

be

a

meaningful

characteristic

if the grid

size

is

large or

if the

elapsed

time

between

observations

is long both

relative

to

the

volume of the

spill.

The

simulated

data

input

capability is

useful for

conducting

contingency planning

environmental

assessment

studies

As noted above,

the

simulated

wind

field

submodels

can

be

highly variable in

complexity.

However,

the

degree

of complexity

is

not

an assurance

of

suitability

for

a

particular

site dependent oil

spill.

Even a

simple

20



TABLE

IV

WIND

FIELD

MODEL

TYPES

Oil

Spill

Model Name

Simulated

Other Measured

Constant

Time

Dependent Spatially

Random

Markov

Dependent

Walk Chain

1.

U.S.

Navy

2.

WGD

3.

Narragansett

Bay

4.

Tetra Tech, Inc.

5. CEQ

6. BOSTM

7.

USCG

(New York Bight)

8. Delaware Bay

9. USCG (New

York

Harbor)

10.

use/API

11.

SLIKTRAK

(SLIKFORCAST,

OILSIM)

12.

MOST

13.

DPPO

(Garver

and Williams)

14. URI

(Georges

Bank)

15. Puget

Sound

16. CAES

17.

Riverspill

18.

NWS/NOAA

19. USCG

(Long

Island

Sound)

20. SPILSIM

21.

EDIS

22. PIC

23.

OSTA

24. OSSM

25. DRIFT

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

21



assumed

but this value can range

from

2.0%

to 4%.

These

values

have been estimated from

numerous

observations

and

experiments.

In

at

least two references,

Madsen

(1977)

and Huang

(1979),

show theoretically that

this

factor

should be

slightly

in

excess of

3%

for deep

water.

The

angle between

the

wind

vector

and

the

wind induced current

vector

is known

as

the

wind

drift

angle.

This

angle

has

been taken

to vary from

to

approximately

20 depending

on latitudinal

influences.

Huang

(1979)

also

shows that

the

wind

drift angle

can

vary from to a

maximum

(which

depends upon the latitude) depending

on

the duration

that

the winds have

been blowing.

This

angle

also

depends

on

the water

depth

and approach a

value of for very

shallow

water.

Surface

Currents

.

Although

wind-induced

drift

currents

are

important

mechanisms in the

transport

of oil

slicks,

they

are

not

the

only ones

of

importance.

Therefore,

we

must

examine the role of residual

and

tidal

currents as

well

as

waves. The

residual currents include

those

circulations

due

to thermohaline and

geostrophic

causes.

In

general,

the

residual

currents

are

most important

for

open

ocean spills

in

deep

water whereas

the tidal

currents

are

most

important

for

near inshore

and

estuary

(tidal)

spills in shallow

confined waters.

In many

models, both

residual

and tidal

currents are

considered

together

and

23



a procedure similar

to

the

wind

factor

approach is

employed

to estimate

the

surface

drift

current. The

factor

most

often

used has

a value of

56%. Many models

are

structured

to utilize

information

on

currents

as

obtained

from

prototype

measurements

or from

estimates obtained

from

circulation

submodels.

The circulation

submodels

are

often major

components

in the oil spill

transport

prediction

procedures.

The

numerical circulation

submodels are not

true

three-dimensional

models;

rather

they

are

two-dimensional

representations obtained

by

making

certain simplifications.

Among others, these simplifications

include

the

averaging

(in

the vertical)

of

the

component velocities.

This

averaging presents

some

difficulty in estimating

the

surface currents

especially

in

regions

where

the

wind

and

tide

are

the

dominant contributors

to the

circulation

pattern. Another difficulty is related

to

the model

boundaries especially where there

is an interface

with

major large

scale

circulations

systems

such as

the

Norwegian current

or

the Gulf Stream.

With

the

exception

of

SLIKTRAK,

none

of

the models attempt

to

model

the

large

scale

circulation

pattern.

SLIKTRAK

attempts

to

model

the

effect

of

the

Norwegian

current by

providing

for acceptance

of predicted values

of

velocities

(presumably

obtained

from another

submodel) at

the

model

boundaries

24



The

state-of-the-art

consists

of

calibrating

the numerical

circulation

submodel with

available field

measurements. The

resulting

currents predicted from

such

a

model

are

then

combined with

wind-induced

drift

to

estimate the

advection.

Subsurface Currents

.

Because

of

the

fact

that

oil

spills

generally

appear

on

the surface, little

attention

has

been directed

to

the

advection

by

subsurface

currents.

It is

generally

believed that

subsurface advection

is

not

an

important mechanism

in oil

slick

transport.

However,

it

is

known

that advection of dispersed

oil

droplets

occurs

as a

result

of

subsurface

currents.

Two

models

include

this behavioral

feature. One is the

DPPO model

(Garver

and

Williams,

1978)

and

the

other is

the

URI

(Georges

Bank)

model

River

Currents

. Even

though

a large

number

of

spills

occur in

river

estuaries or harbors

where

there is

substantial

fresh

water inflow

as

well as other

currents,

this

aspect of

oil

spill

transport

has

received

little

attention.

One

model, Riverspill, was

developed

specifi-

cally

for

river-type spills (Mississippi

River)

.

Considerable

effort has

been directed

toward

determination

of advection

by

river

currents.

Another

model,

USCG

(New

York Harbor) has

also been

developed

to consider

the

fresh

water

inflows from the

Hudson

River.

Both

25



models

ha.ve

been

calibrated

by

comparison with

numerous

field

observations.

Waves .

Advection

by

waves

directly

or

by currents

generated

by waves

is one of

the

least

understood

aspects

of

oil

spill transport. Some

authors believe that it is

an

important

mechanism but

only

three

models

(SLIKTRAK,

Delaware Bay and USC/API)

have

recognized

the possibility

of considering

its

effect.

In

summary, advection is

one

of

the

most

important

processes

by

which

oil

spills are transported.

The

prediction

of

advection resolves into

a

determination

of the

wind and

current

fields.

From

a

knowledge of

the

wind and current fields,

a

n\M:iber

of

numerical techniques

have

evolved

from

which

advection of

oil

spills can be

made.

The

role

of

subsurface currents is

probably not

important

in transport

of

large

oil slicks

but very

important

in

advection

of oil

droplets.

The

contribution

of

waves

to

the

advection

process

is very

poorly

understood.

Spreading and

Dispersion.

We

consider

spreading

and

dispersion together

since

these

mechanisms

are

responsible

for

the growth

of an

oil slick

after the

initial

spill.

During the

initial

stages,

spreading

is

Not to

be

confused with emulsif

ication

or

oil-in-water

formulation

of

droplets.

26



clearly the

most important

of

these mechanisms.

Spreading

is dependent unon

the

oil

properties

at

the

time of

the

spill

whereas

dispersion depends upon

the

external shear

forces

acting

on

the

oil spill

surfaces.

A

number of

investigators (e.g., Stolzenbach,

et

.

al

.

,

1977) have shown

that,

for

a

given

spill volume, after

a

certain time, the

dispersion

process becomes more important

than

spreading.

There

are essentially

three

distinct

approaches

that

are

employed

in

the

treatment

of

spreading

and

dispersion.

Table

V presents

a

listing

of

the

spreading

submodels

that

have

been

employed by the

oil

spill

models

that were

available

for

review. Most of

the

models that

treat

spreading

do so by using

a

method that is

related

in

some way to Fay's

(1971)

theoretical

analysis

of

spreading. Some

models combine

Fay's spreading

analysis

with

a

diffusion

approach. Other models

consider

the

growth

of

oil

slicks to be dominated

by

diffusion

aspects

and

ignore altogether

the role of

the

oil

properties

such

as

surface

tension. For example, the

Delaware

Bay

model

substitutes

a

diffusion equation

in lieu of

the

third

stage

(viscous-surface

tension)

of

Fay's

(1971)

three-regime

spreading

model. As another

example,

the

use/API

model

eliminates the second

stage

(gravity-viscous)

of Fay's

(1971)

model

altogether.

As

mentioned

above,

a

few

models

treat

;

he

growth

of

oil slicks solely by

27



TABLE

V

TYPES

OF SPREADING

MODELS

Oil Spill

Model

Name

Fay's

Spreading

Theory

Fay's

Spreading

with

Diffusion

Diffusion

Theory

Independent

Statistical

or

Numerical

Treatment

Narragansett

Bay

Tetra

Tech,

Inc.

BCSTM

USCG

(New York

Bight)

Delaware

Bay

USCG

(New

York Harbor)

use/API

SLIKTRAK

(SLIKFORCAST,

OILSIM)

MOST

DPPO

(Carver

and Williams)

URI

(Georges

Bank)

Puget Sound

CAES

Riverspill

NWS/NOAA

USCG

(Long

Island Sound)

EDIS

PIC

OSSM

DRIFT

X

X

X

X

7

X

X

X

X

X

X

28



means of a

diffusion

theory such as that developed

by

Murray

(1972)

or a random

Fickian

diffusion

model.

The

rationale

for

this is based on observations of

oil

spills

that are

continuously discharging

(i.e.

,

versus

instantaneous

spills)

wherein

it was

concluded

(Murray,

et.al.

1972)

that the

growth

a

short distance

from the

source, was

controlled by

the

horizontal eddy

turbulence

rather

than

surface tension

effects.

For

example,

the

USCG

models

use Murray's

turbulent

diffusion

theory while

DRIFT

uses a

random Fickian diffusion

approach

.

One approach

which is decidedly

deterministic

is the

NWS/NOAA

model wherein

a

numerical

solution

of

the

equations

of

motion

(oil)

is envisioned.

At

the

opposite

end of

the

philosophical spectrum is

the

Pudget

Sound model which is

best described

as an

indepen-

dent statistical

(probabalistic)

model. It

is based

on

the use

of

a system of empirical

regression

equations.

In

this

connection, all of

the

models

that treat

spreading-

dispersion

with

a

diffusion

theory

in

any

way

require

some evaluation

of a

set

of

diffusion/dispersion

coefficients. In

general, these

coefficients

must be

obtained

empirically

or

from

published

values

which

have

been

obtained from experiments.

In some cases,

where

there are

actual

observations

of

oil spills, the

29



diffusion coefficients have

been

employed

as

calibration

coefficients. This

is

illustrated

by

the

USCG (New

York

Harbor)

model.

From

a

theoretical

viewpoint,

those

models which

treat

spreading-dispersion

by use of

Fay's

spreading

theory

in

combination

with

a

diffusion

approach are

probably

superior

to

the

other approaches. However,

all

of

these

models do not treat

spreading-dispersion in the

same way

because

there

are

some subtle,

minor differences

in

their

procedures which may

have

profound

consequences

in

the

results. As

a general observation,

none of

the

models

contain

any

provision for eliminating

or

evaluating

the

numerical

errors

that may

be present.

This

is an

important

consideration in the treatment

or

diffusion/dispersion

because of

the

possible contamination of the

real

physical dispersion with

numerical dispersion.

The

latter

is merely an artifact of the computational

scheme whereas

the

former

is

real.

This

is clearly

illustrated in the

case of

the

Tetra

Tech,

Inc.

,

model

about

which

Stolzenbach

, et .

al

.

(1977)

has

commented in

some

detail.

One interesting

treatment of


is

the Delaware

Bay

model

in which the

third phase of Fay's

three-regime spreading model is replaced

by

a

compatible

diffusion

model. The

justification

for

making

this

substitution

stems

from the

observation

that

whereas

the

30



third

phase

exists

in laboratory

situations

(where the

background

turbulence

levels

are

low)

,

no

such conditions

exist in

the

real

world.

Therefore, in the

prototype case,

the

higher turbulence

levels

require

the

existence

of

a

diffusion

approach.

This

justification seems

very

rational

and

plausible and is

consistent

with

Murray's

et.al.

(1972)

observations

and

conclusions.

In summary,


is an important

mechanism

for

the transformation

and/or

growth

of

oil

slicks.

In

the

early

stages,

spreading

is

the

dominant

process whereas after

a

critical time

(for

a

given volume)

dispersion

seems

to predominate. Models

which seem best

suited for

a wide

variety

of time-dependent

situations

are

those which combine Fay's spreading theory

with

a

diffusion

approach.

Two

extreme cases

can

be noted.

In

confined nearshore

areas,

where

the

time and

distance

scales are relatively

short

,

a

model which employs

only

Fay's

spreading approach would

be

quite

valid.

In

a

similar

way for regions

where the

time and

distance

scales are

relatively long,

such

as

far

offshore, a

model

which

employs

only

a

diffusion theory would

be

valid.

In

the

case

of

the

latter,

an independent

statistical

or numerical

approach

might

also be

considered.

In

any of the

diffusion-statistical-

or

numerical-based

submodels,

the

degree of numerical

diffusion

(or

dispersion)

should

be

determined.

31



Evaporation.

Although

evaporation

is known

to be an important

factor

in

the f

£,te of

oil spills

—

especially

in

the

case

of

spills

far offshore,

it has

received

less

attention

from

modelers

than

the

other

processes.

Only six

(6)

of

the

models reviewed

include

an

evaporation submodel.

Moreover, because

evaporation

usually occurs

in the

presence of other weathering

processes

such

as photo-oxidation,

dissolution,

biodegradation and

sinking and

sedimentation,

it is

difficult

to

make

..

reasonable evaluations concerning

the

appropriateness

of

the

evaporation

submodels. Of

the

oil spill models

reviewed, there seem

to

be

no essential differences in

the

manner

in

which evaporation

was

estimated.

In

general, an

evaporation

function

or decay

rate is

derived

from

the

main

factors

which

affect

the

evaporation.

These

include:

(1)

the

vapor

pressures

of the

various

oil

fractions,

(2)

the

size

of

the

spill

(area

and

thickness),

(3)

the

evaporative

mass transfer

coefficient,

and

(4)

the environmental

(climatic)

conditions,

including

wind speed.

All of the

submodels employed a

mass transfer

coefficient but

some

did

not

consider the

spill

area

or

slick

thickness in their

evaluations.

These

are

indicated

in Table

VI.

Also,

the

basis

for

the

submodel

can

be

categorized

as

being

empirical

;

experimental- or

theoretically-related.

These

are

also

indicated

in

Table

VI

32



TABLE

VI

CLASSIFICATION

OF

EVAPORATION

SUBMODELS

Oil Spill

Model

Reviewed

Type

Area

Considered

Slick

Thickness

Considered

use/API

SLIKTRAK

(includes

SLIKFORCAST

AND

OILSIM)

Theoretical

Experimental X

DPPO (Carver

Empirical

-

and

Williams)

URI Empirical

X

(Georges

Bank)

CAES

Experimental X

DRIFT

Empirical X

33



In

summary, only

a

few

models

attempt

to

evaluate

evaporation

in

spite

of

its importance

to

the

ultimate

fate of

oil

spills.

Unfortunately,

there is

insufficient

data to permit a

rigorous

evaluation

of

the

various

approaches

.

34



Chapter

4

Evaluation

of

Oil Spill

Models

for Use in

North

Carolina

Waters

In

order

to

select a

suitable

model

or

family

of

models

for

predicting oil spill behavior in

waters located

within and

adjacent

to

North Carolina, it is necessary

to

identify the physical characteristics (and

associated

mechanisms)

that

(1)

govern

this behavior and

(2)

serve

as adequate descriptors

of

the referred-to waters. The

analysis

carried

out

by

Stolzenbach, et.al.

(1977)

and

summarized

in Chapter

2

,

provides a

convenient

means of

identifying

these

features, but

it is

not

the

only

means.

An order of magnitude

analysis

of the governing equations

could

also

be

carried out .

But

, it is very

convenient

to use

the

work of Stolzenbach. Moreover, it provides a

clear visual representation of the conceptual

framework.

Therefore,

we

can

utilize Figure

1

which indicates

the

major

mechanisms of importance to

oil

spill movement

in terms of

time

and

length

scales. We

can

immediately

realize that

two additional

types

of

information

are

needed to

complete

our

analysis.

One

is

a

parameter

that

describes

North

Carolina

waters.

For

any

given

spill

locality,

the

parameter

that

seems

natural

is

the

minimum

distance

from

the

spill source

to

shore

35



(i.e.

,

x-number of

meters). This

can

be

used to describe

localities in inland waters

(in the Cape Fear River,

for

example) or

localities

nearshore

or

localities

far

offshore

(an

oil

drilling

platform,

for

example). For

estuaries,

bays,

inland

waters

and

other confined

or

semi-confined

waters,

these

distances

can be

scaled from

any

hydrographic

chart. We

can

assume

that

a

value

of

from to

500 meters would be

a

reasonable value

to

use

to

describe

these

waters. To distinguish

between

near-

shore

and

offshore

areas

,

we can adopt

the

arbitrary

criteria

that offshore

areas

are those

beyond

which

shoreline

impacts from

tidal

currents

are virtually

non-existent.

On this basis,

we

can

make

the

following

descriptions

for North

Carolina

waters

in terms of

single-length

parameter:

Inland

waters and

estuaries

to

500

meters

Nearshore

areas . .

to

1000 or 10,000

meters

Offshore

areas

....

>1000 or

10,000

meters

These values

are not to

be

construed as

actual

distances

of

any specific

locality

but are

generally

representative

of

dista,nces

that

characterize

the

indicated

regions

for the

purpose

outlined

above.

The

other

source

of

information

that

is

needed

is

derived from

climatic

data

for

the

indicated

regions.

Again,

precise

values

are

not

needed;

only

an

order of

36



magnitude

is

required.

For

this

purpose,

we can assign

the

following

values

of advection

velocities

(in the

direction

of the

distances

indicated above)

for

the

three

regions.

Inland

waters and

estuaries 0.1

/sec

-

1.0 /sec

Nearshore

areas 0.01

/sec

-

0.1

/sec

Offshore

areas 0.001

/sec

-

0.01

/sec

More

precise values

can be

obtained

from

detailed

examination

of the

climatic

data (wind and currents).

The above

advective

velocities are related

only

indirectly

to

the

actual wind-induced

surface currents

and/or tidal

or residual

currents

since we

are

interested

only in that

component taken

parallel to

and along the

minimum

trajectory

path

from

spill source

to

impact

location

These

features

can be

illustrated

by referring

to the length-time

scale diagram shown in

Figure 2. First,

consider

a

spill

in an

estuary

or

inland

waterway

where

the

characteristic

length is

500 meters

and

the

characteristic

advection

rate

lies somewhere

between

1.0

and

0.1

meters

per second.

We

can

see

from

Figure 2

that

the

total

elapsed

time

from

spill

to

impact

is

rather

short

ranging

from 425

to

4100

seconds.

Figure

2

shows that

dispersion can

be neglected

and

we

also

note

(from

other

information)

that evaporation

occurs

along

with

other

processes

37



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38



throughout

the

growth

and

transport

of

the

slick.

However,

evaporation

and

the other weathering

processes

are

still

in

their

early

stages

of

development

by the

time

of

impact.

Therefore,

modeling of oil spill behavior in

estuaries

and inland

waters

should include

the simulation

of

advection, spreading

and

evaporation.

From

a

knowledge

of additional

details

concerning

the

spill, such

as

spill

volume,

and

properties of the

spill

material as

well

as

detailed climatic

conditions, we can

evaluate

the

relative importance

of

the

growth (i.e.

,

spreading)

or

transport

(i.e.,

advection) activities

in

causing

impacts.

For example, as

a

general

trend

for fixed

advection

rates,

the

spreading activity increases in importance

with

increases in

spill

volumes.

Finally,

consider

an offshore spill at a

distance greater

than

10,000

meters

from an

impact

location

and

with

characteristic

advection rates

less

than

0.01 meters

per

second. On

this

basis

we

can

determine that

the impact

time is greater

than

830,000

seconds

or

230

hours

(almost

10

days).

We

take note

of

the

fact that dispersion

is the

dominant

process in

the

growth

of

the

slick and

that

spreading

has

been completed.

Evaporation

has

been completed.

In

some

cases,

advection

may be an

important mechanism

39



but

advection by tidal

currents

is

unimportant

by

definition.

Evaporation

has been

completed.

Therefore, modeling

of spills in the

offshore

region

should

include advection,

dispersion

and

evaporation.

Dispersion

is very important

but

advection

by

tidal

currents,

in

general,

can

be

neglected.

Next, consider

a

spill

in

the

nearshore

region

(as

defined

above)

such that

the

characteristic length

has

a

value

of between 1000 and

10,000

meters

and characteristic

advection

rates

of

between

0.01

and 0.1

meters.

Again,

using

Figure

2

,

we

can

determine that the elapsed

time

from

initial spill

to

impact

varies

from

7700

to

83,000

seconds for

the

1000 meter distance, and

from

83,000

to

830,000

seconds

for

the

10,000

meter distance.

In

the

first

instance where the

distance from

the

spill

source

to

impact

is

1000

meters,

we see

that

spreading

is almost complete and dispersion

has

not

yet

become

effective

whereas in

the second instance

(where

the source-impact

distance is

10,000

meters),

spreading

has

been

essentially completed and

dispersion

has become

an

important activity

—remember

that

scales are

logarithmic.

In spite

of the

apparent

low

advection

rates,

the

transport

process

(including

advection

by

tidal

currents) plays

an

important

role in determining

the time of

impact.

Evaporation

has

been

active throughout

and, in

the

case

of

40



the longer

impact

times,

essentially

has been

completed.

Other

weathering

processes have become significant.

From

these

observations,

then,

we may

conclude

that

modeling

of

oil

spills

in

the

nearshore

region

should

include provision

for simulating advection,

spreading,

dispersion

and

evaporation. Advection by

tidal currents

should definitely

be included

in the

modeling

scheme.

From

the

foregoing,

we

can

list

the

modeling

requirements

for the

various

regions.

Inland

waters and

estuaries

Advection

,

spreading

,

evaporation

Nearshore areas Advection

,

spreading,

dispersion, evaporation

Offshore

areas Advection, dispersion

,

evaporation

As

stated

in the Introduction,

one

of

the

goals

of this

study is

to

evaluate and select

models for the

prediction of oil spill behavior in North

Carolina

waters

As

implicitly

suggested,

the possibility

of

identifying

a

single

model, while

attractive on a

superficial

level,

is

not realistic.

Among other objections,

the

use

of

a

single

model

for

solution

of

all

cases

of

interest

would

require

use

of

the most complex

and

sophisticated

model

for all

cases.

Therefore, it

would

be

too expensive

41



for

the

simplest

cases and might

require

input

data

that

is

not even

available. Thus,

the

approach has been

to classify the number

of

cases into

the

categories

of

inland waters

and

estuaries,

nearshore

areas

and

offshore

areas. Within

these

categories, we

have

attempted to

identify

families of

models which

would

be

appropriate.

In other

words,

there

has

been an attempt

to gear

the

model solution

capability

to

the

problem requirements.

At

this

stage,

we

can

drop from further

consideration

the

U.S.

Navy,

WGD,

CEQ,

SPILSIM

and

OSTA

models,

since

they

treat

only

advection. The

WGD model

has

been

applied

to offshore spills

and

the CEQ model

has

been

applied

to both nearshore

and

offshore spills

but

there

are

other

models

that

include

the other

processes

as

well.

The same is true

to a

lesser

extent

of

SPILSIM

which

was

developed for application to

the

special

case

of

the Great

Lakes

.

We can then reclassify

Cin

a

subjective way)

those

models

that are suited for

the three

regions of

interest.

This is shown in

Table

VII,

where

it will be

noticed

that

some

models

can be applied to

more

than

one

region.

42



TABLE VII

CANDIDATE MODELS FOR

APPLICATION

TO

NORTH CAROLINA WATERS

Inland Waters

and Nearshore

Offshore

Estuaries

Narragansett

Bay

USCG

USC/API

Tetra

Tech, Inc.

(New York B

ight)

SLIKFORCAST

Delaware Bay

BOSTM

(SLIKTRAK)

USCG

(New York Harbor)

CAES

Delaware Bay

URI

(Georges

Bank)

Puget

Sound

use/API

DPPO

(Garver

and Williams)

Riverspill

USCG

URI

(Georges

Bank)

NWS/NOAA

(Long

Island

Sound) DPPO

EDIS

PIC

(Garver and Williams) OSSM

EDIS

MOST

PIC

DRIFT

OSSM

DRIFT

43



Inland Waters

and

Estuaries.

As

shown in

Table VII, we

have

some

eight

(8)

candidate

models

for

possible

application

to

North

Carolina.

The

USCG

(New

York

Harbor)

model

has

been well

calibrated by

a

number

of

oil spills in

New York

Harbor

but it

requires

a

comprehensive

knowledge of the

fresh

water inflows (Hudson

River)

and

dispersion

coefficients.

Fortunately for New

York

Harbor,

thanks

to

the intense

interest

over

a

long

period

of time, this information

is

available.

Essentially,

the

USCG

(New

York

Harbor) and

USCG (Long Island

Sound)

models

are empirical

type

models

which

have

the

advantage

of

having been

calibrated

by

numerous observations

and

therefore have been validated.

Such information is

generally not

available for

North

Carolina

waters.

The Narragansett Bay

model

is

a

simplistic

easy-to-understand

model that could

be

applied

to

North

Carolina

inland

waters.

However,

two changes

would have

to be

implemented.

The wind drift angle

would have to

be

changed

to

something

other

than

20

and

the

spill-spill

interaction

effect

would

have

to

be taken

into account

for

non-instantaneous

spills.

The latter may require

a

substantial

reprogramming

effort

Although

the

Tetra

Tech, Inc.,

model

has

been

applied

and calibrated to

San Pedro

Bay,

California,

44



there

are a number

of

reasons

why this model should

not

be

considered

for

application

to

North Carolina waters.

These

reasons

are

given in

a

review by

Stolzenbach,

et.al. (1977), but the

major

reason

is

that the

dispersion

is

a

numerical dispersion

that is

not related

to

the

physical

dispersion,

if

it

exists.

The PIC model

is

theoretically sound and

a very

fundamental

approach

but the difficulty with

this

model

is that

it

has

not been proven or

validated.

The

remaining

three

models

(Riverspill,

Delaware

Bay

and

Puget Sound)

constitute

the

three

candidates

for potential

application to

North

Carolina

inland

waters. All three models have more

or

less been

validated by

comparison

with

actual spills

or

simulated

exercises.

Riverspill

was

developed

for

the

situation

on

the

Mississippi

River

and

is

the

simplest

of

the

three

models to

implement.

Although it is

intended

for

the

situation where

there is substantial river

current

,

there is no

reason,

in principle, why it could

not

handle

the situation of

tidal

currents.

Riverspill

is

highly

deterministic whereas

the Puget

Sound model

is

statistical

in

nature.

The

Delaware

Bay

model is

also

a

deterministic

model

and

one

that might

prove

to

be

better

suited

to

handle

those cases

of spills

at estuary

junctions

with

45



the

open

ocean.

Unlike

the

other

two models,

it

includes

the advective drift

due to

waves

as well

as

dispersion.

One

of the

difficulties

in

using the

Delaware

Bay

model

is

that

the

diffusion coefficients

must

be

known

or

assumed.

In

summary,

the following

models

seem well

suited

for the prediction

of oil spill behavior in

North Carolina

inland

waters and

estuaries. These

are

the Delaware

Bay model, Puget

Sound model

and

Riverspill.

Nearshore.

Some

eleven

(11)

models reviewed

were selected as

potential

candidates

for

modeling

spills

in

the nearshore regions

of

North Carolina. For

a

niimber

of reasons, this is

the

most difficult

region

to model.

On

the

one

hand,

a

very

large area offshore

must

somehow

be

considered and

often this

can

only be

done at

a

very

crude scale.

On

the

other

hand, in order to

make

meaningful

evaluations,

modeling of

details near

coastal

impact

locations requires

a

smaller,

finer

scale.

The

result

is

that none of

the

models

listed

in Table VII

can be applied with

confidence

directly

to

North

Carolina

waters without some

modification.

The

USCG

(New

York

Bight)

has

been

applied to

the

study

of

spills off

the

Delaware

and

New

Jersey

coasts

46



but it has

been only partially

validated. Moreover, as

noted by

Stolzenbach,

et . al

.

(1977),

many

details

are

lacking

and some of

the

assumptions

cannot

be justified.

Neither

the

BOSTM

or

CAES

model

actually

treat

dispersion

(in

a

strict

sense), and

the

BOSTM has

the

additional disadvantage in that

it

does

not

consider

any

of

the

weathering

processes.

For continuous

spills,

the

BOSTM model

neglects

spreading,

whereas,

the CAES

model

neglects

the spill-spill

interaction

effect.

However,

results

of

both

models

have

been

applied

to

prototype oil spills

or

to

simulated spills.

If

weathering

processes

were added to

the

Delaware Bay model, it is

possible

that this model

might

be

adapted to

the nearshore regions off the North

Carolina

coast.

Other comments regarding

this

model have

been

provided in

the

previous

section.

The

USC/API

model is a very

comprehensive,

composite model

, but the

model

as a

whole

has

not

been

validated by comparison with prototype

spills.

Moreover,

many of

the component parts are somewhat

dated.

More

up-to-date

information is available that

could

be

used

in this model.

The

EDIS

model

has

been applied

to the oil

spill

in

Campeche

Bay

(IXTOC-I)

and

to

the Argo

Merchant

spill

but

insufficient

details

are

available

to

evaluate the

47



models

reviewed

can be

applied without

some modification.

The following

models

seem best

suited

for

this

purpose:

DRIFT.

URI

(Georges Bank), and DPPO (Garver and Williams)

With

slightly more

modification,

the

Delaware

Bay

model

might

also

be

a possibility.

Offshore. Recall

that

for

the

offshore

region,

spreading and advection due to tidal

currents

can, in general,

be

neglected. As a result of

these

simplifications,

modeling

of oil

spill

behavior

in

the

offshore

region

tends

to

be

somewhat less

difficult than

in the

nearshore

region,

all other

factors

being equal.

Models

which

are

appropriate

for the

offshore

region

are

listed in Table

VII.

Comments

regarding

all

of the

models

except

three have already

been provided.

One

of

the deficiencies of

the MOST model

is that it

does not

take

into account evaporation.

It has

been

applied

to

the

BRAVO

blowout

(North

Sea)

but

the

agreement

with

observations needs

substantial

improvement

The

NWS/NOAA

model is still under development

but

when

completed will

probably represent the most

comprehensive

and

fundamentally

sound basis for

predicting

offshore

oil

spills.

The

remaining

model,

SLIKFORCAST

(SLIKTRAK)

has

been

employed to

simulate

the

BRAVO blowout

and

the

predictions

seem

to compare favorably

with observations

49



at

different

locations.

SLIKFORCAST

is

a very

comprehensive

simulation

program

which

can

be

used

for both

contingency

planning

and

emergency

tracking.

The structure

of the

program

is in

many

ways

similar

to the

DPPO model

(Graver

and

Williams

)

.

In

summary,

SLIKFORCAST

appears

to

offer the

greatest potential

for modeling of

oil spills

in

the

offshore

region.

However, the NWS/NOAA

model, when

completed

and validated,

may be

equally

or better suited.

As

secondary

choices,

the

DPPO

model (Garver

and

Williams)

and URI

(Georges

Bank)

might

also

be considered.

All

of

the

foregoing

models

require

a

certain

quality

of

climatological and

oceanographic

data for

input

in order to

obtain

reasonable

predictions.

Nearly

all of

the

models employ

a

numerical approach utilizing

a

given

areal

mesh

of

fineness

ratio

such

that

the

following

two

requirements

are

satisfied. One

require-

ment is

that

the

spacing dimension

be small

enough

so

that

all important

and relevant

details

are

known.

In

practical

terms, this

translates into

selecting

a

mesh

size

that

utilizes

all quality

environmental data.

The

other

requirement is

that

the

area covered

be

large

enough

so

that boundary

effects

are

minimized.

The

latter

introduces

another

restriction

in

that the

mesh

spacing

cannot

be

too

small; otherwise,

a

system

5Q



involving

an unmanageable number of equations

must

be

solved

simultaneously at

each time

step.

At

the

same

time, both the

time

step

and

the

spacing must be

selected

in

order

to

minimize error

propagation.

The

data

of

most concern is that

which

affects

advection

and

dispersion. Advection

is

determined

from

the wind

field,

surface

currents

and

subsurface currents

and to a

lesser extent

by

the

wave

field.

Although each

oil

spill

model is

affected

somewhat differently

by

the

quality

of the

input

data, the

relative evaluation

of

the models is not very sensitive

to

data

which is

available for North Carolina

waters.

Therefore,

only

a

fevi general observations

concerning

this

data

(as

obtained

from

a

review of the

available open

literature) are made.

As

a general rule,

wind

information

appropriate

for

North

Carolina

inland

waters

and

estuaries

and

for

the nearshore

region is

very poor.

Wind

data for

the

offshore region is only marginally better.

Wind

data

for

the inland waters

and

estuaries is

based on

extrapo-

lation

of

data

collected from

nearby airports whereas

that

for the

offshore

region

is

based

on

ship reports.

Obviously,

the

geographic distribution

is

not

uniform

since

it

is

biased

in favor

of

the more

heavily

traveled

shipping

lanes.

51



The

quality

of

current

data

for

the

inland

waters

the estuaries is

highly variable.

Current

due

to tides

in

some

locations (i.e.,

Cape Fear

River estuary)

is

adequate.

In

other

locations, such

data

is

spotty.

Currents

due

to

fresh

water

inflows

is

also highly

variable.

The quality

of

current

data

for the

nearshore

region is

also

highly

variable.

In

the

case

of

the

offshore

region,

the three-dimensional

circulation

pattern for

currents

appears

to be

adequate

for

that

portion south

of

Cape Hatteras.

At

the

same

time,

knowledge

of

the

circulation

pattern

for that portion north

of

Cape

Hatteras

is

only grossly known

or,

at

best,

uncertain.

The

foregoing comments are based

on

a

review

of

a

large number of references including

but

not limited to

those cited

in

connection with the Draft

Environmental

Impact

Statement , Proposed

1981

Outer Continental

Shelf Oil

and

Gas

Lease Sale No.

56,

Bureau of

Land

Management

Outer Continental

Shelf

Office, New Orleans,

Louisiana. Among those

references

reviewed

were

the

following in-house

reports not

available for general

distribution

at

this time (July,

1982).

1.

Kantha,

L.H.,

A.F.

Blumberg,

and

G.L.

Mellor

A

Diagnostic Technique for Deducing

the

Climatological

Circulation as

Applied

to

the

South

Atlantic Bight

,

Report

No. 69

Dynalysis of

Princeton, Prepared

for

Bureau

of Land

Management,

U.S. Department

of

Interior,

Contract No.

AA551-CT-9-32

,

1981.

52



2. Kantha,

L.H,,

A,F.

Blumberg, H.J.

Herring,

and

G.L. Mellor,

The

Physical

Oceanographic

and Sea

Surface

Flux Climatology

of the

South Atlantic Bight

,

Report No.

70,

Dynalysis

of Princeton,

Prepared

for Bureau

of

Land Management,

U.S.

Department

of

Interior,

Contract

No.

AA551-CT-9-32

,

1981.

3. Blumberg,

A.F.

and

G.L. Mellor,

Circulation

Studies

in the

South

Atlantic

Bight

with

Prognostic

and Diagnostic

Numerical

Models

,

Report No.

71,

Dynalysis

of Princeton,

Prepared

for

Bureau

of Land

Management

,

U.S. Department of

Interior, Contract

No. AA551-CT-9-32,

1981.

4.

Blumberg,

A.F.,

H.J.

Herring,

L.H.

Kantha,

and

G.L.

Mellor, South Atlantic

Bight

Numerical

Model Application--Executive

Summary-

,

Report

No.

72,

Dynalysis

of Princeton

,

Prepared

for

Bureau

of

Land

Management, U.S.

Department

of

Interior,

Contract

No.

AA551-CT-9-32

,

1981.

These

reports were made available

to

the

author through

the efforts

of

Mr.

Eric

Vernon, Office

of

Marine Affairs.

In

summary,

there

is

a

need

for

additional coastal

wind

buoy

station data

and

for improved

knowledge of the

current

circulation pattern offshore north

of Cape

Hatteras

53



CHAPTER

5

Summary

and Conclusions

A brief

history

of

the state-of-the-art

in

oil spill modeling

has

been

presented in

Chapter

2,

along

with

an

outline

review

of

the

fundamental

problem

development

as

stated

in

mathematical terms. It

has

been

shown

that

the

major processes which

have greatest

influence

on

impacts resulting

from

oil

spills

are

advection,

spreading.-,

dispersion

and evaporation,

but

that

all

of these processes

are

not

necessarily

active

in

all cases.

A review and

classification

of

various

models

as

they

are

published in

the

open literature is

presented

in Chapter

3.

Detail

reviews

for

each

modeling

effort

are

presented in the Appendix. For each modeling effort, the

name

or description of

the

model is

presented along with

the

primary reference(s)

and

corresponding

abstract(s).

Reviewer's

comments

are also presented.

Chapter

4 contains

an

analysis establishing

the

criteria

for evaluating oil

spill models for use

in

North

Carolina

waters.

This

is followed

by

an

evaluation

of leading

model candidates

for

each

of

the regions

into

which

North

Carolina waters may

be

classified.

54



RECOMMENDATIONS

As

a

result

of this

study,

a

number

of

findings

and

observations stand

out

which

could

easily

be

formulated

into

a

set

of recommendations.

Rather than

present a

formal

set of

recommendations

(which

always

reflect

the

biases of

the

author)

,

the

nature

of the

study is such

that it is

believed

to be more

appropriate to

simply

present

the most

important

observations and let

the

reader

form

his (or her)

own

recommendations.

These

are

as

follows:

1. For

North

Carolina regions,

there

are

two

major deficiencies which inhibit

application of

the

more

sophisticated

models (including those now

available

and

under development)

in

order

to

realize maximum benefits.

One

of

the

deficiencies

has

to

do

with the data

base (climatic

and

oceanographic)

which

is

not sufficiently

fine

in

order to

make

detailed

coastal

evaluations

of

oil

spill

impacts with reasonable

confidence.

The other has to do

with

the lack

of

detailed knowledge

concerning

resource

inventories

(both living

and

56



non-living)

and

their

exposure

to

various

oil

spills.

2. As

a

general

observation,

both

short-term

and

long-term

weathering

processes

are

very

poorly

understood.

This will require

a

deliberate

and sustained

research effort

at

the

national level.

3.

None of the models reviewed

treat

the

problem

of

continuous spills

in

a

rigorous

manner.

All

of

them

make

some

assumptions

which introduce

errors into

the analysis.

4. There

are

a

large number of models

available

and

under development. It seems

more

prudent

to

adapt

existing

models

to

new

situations

rather than embark

on

a

new

model development

program.

This

is true even for

the

nearshore

zone

where

,

in

general , most

models

are

inadequate.

Adaptation

of

existing

models

to North Carolina

waters

still remains

a

challenging

task,

however.

5. It

is

unlikely

that

any one

model can

be

developed

or

adapted

that has

general

applicability

to a

wide variety of

situations. It is more likely

that

a

single

family

of

models can be

developed,

57



all with similar procedural

characteristics,

to

meet

this

need.

Therefore,

the

attempt

to

develop or

to

find

a

single

model

to

meet

all

needs

is

probably

a

fruitless

endeavor.

As

a

by-product

of

this

study,

it was

observed

that

there is a

tremendous

communication

(or

understanding)

gap

between

various

factions of

different

communities

concerning the

matter

of

oil

spills

and

their

impacts.

This

includes both federal

and state

administrators and

decision

makers,

scientific

community,

industrial

community,

local

community leaders ,

concerned

populace

and

various

state

and

local

politicians.

58



APPENDIX

6.0



APPENDIX

This appendix

contains summaries for

each of

the

modeling

efforts

identified

during

the

course

of

this

investigation.

The

original publications,

which

describe

and

provide

details on the modeling

efforts,

have

been

collected

and reviewed

in all

but

three

cases.

For each

effort, the summaries list

the

model

name

or

description

followed by

the

primary reference(s)

and

by

the author's

own

abstract

or one

synthesized by the

reviewer.

The

reviewer's

own

concise comments

follow

the abstract.

In

the cases of

the three

exceptions

(BOSTM,

use/API,

and

MOST), the

abstract is not

given and the

reviewer's

comments

are

based

on the numerous

comments

provided

by other reviewers

or isolated

comments

appearing

in the

open

literature.

The

BOSTM and

USC/API

models

have

been

reviewed

comprehensively by Stolzenbach,

et

.

al

.

(

1977)

.

Unfortunately, in

spite

of

a

deliberate

and

dedicated

search

by

several of the

area

librarians,

the

primary

references

appropriate

for

these

three

models could

not

be

obtained

in

a

reasonable period of time.

In one case,

the reference

was

simply out-of-print and

in

another case,

permission

to release the

reference due

to

proprietary

restrictions

has

not yet been

obtained.

61



Finally, the 1981 Oil Spill Conference

is

scheduled

for

release

in

September

1982

and

will

contain

additional

material

relevant to

these models.

The

order

in

which

the

modeling

efforts

are

presented

is a

historical

one

with the

earliest

developed

models

appearing

first.

62



Model

Name

or

Description

U.

S.

Navy

Reference

Webb, L.E.,

R.

Taranto and

E. Hashimoto,

Operational

Oil Spill

Drift

Forecasting

Seventh

U.S. Navy Symposium on Military

Oceanography, Annapolis, Maryland,

1970

Abstract

Recent

incidents

of large

scale oil

pollution

have

had

catastrophic effects on the

ecology,

recreation

and wild life

resources

of

coastlines and

coastal waters

and caused worldwide public opinion

to be

very

sensitive

to

this problem.

Fleet

Weather

Centrals should

have the

capability

to provide

movement

forecasts

for

oil spills

from naval vessels or other

sources,

identifying

the

area

of

maximum

threat

and permitting containment

action

to

be

taken

most efficiently. A tentative method

is

presented

using

surface current

parameters

based

on

operational

data

available

at

most

Navy

Fleet

Weather

Centrals

.

The

surface

current parameters influencing

oil

spill drift

used

in

this proposed forecast

method

are

permanent

currents,

wind

drift,

geostrophic

and

tidal

currents.

A

basic operational

forecast

using

the

vector

sum of the pertinent

parameters

is presented.

Modifica-

tions

of the

basic forecast method

due

to

the

location

of

the spill

(open water,

restricted

water)

are

explained,

The

method presented

should

provide

an acceptable

forecast

as an aid

in effective control

or

containment

of

oil

spillage.

Reviewer's

Comments

This

is

one

of

the

earliest

models

proposed

and is

a

very

simple

advection-only model.

The advection

is

taken

to

be

the vectorial

sum

of

the various

currents

which

are assumed

to

consist

of

permanent

geostrophic,

tidal and wind-drift

types.

This

model

is

one

of those

reviewed

by

Stolzenbach,

et

.

al

.

(1977).

63



Model

Name or

Description

Warner,

Graham,

Dean

(WGD)

Model

Reference

Warner,

J.L.,

J. W.

Graham

and

R.

G.

Dean,

Prediction

of the

Movement

of

an Oil

Spill

on

the Surface

of

the

Water,

Paper

No. 1550

Preprint

of

the

Fourth Annual

Offshore

Technology

Conference,

Houston,

Texas,

May

1972

Abstract

A calculation

procedure

is

described

to represent

the

displacement

of a

surface

oil spill

under

the action

of

time-varying

surface

wind

stress

components;

predictions using

this technique

are carried out for the 1970

Arrow

spill in

Chedabucto

Bay,

Nova

Scotia.

The

procedure presented is

based

on

a

convolution

integral

of

the

x-

and

y-

components

of

a

time-varying wind

stress

and is

approximated

in

summation form for computer

application. For an impulsive wind stress, it

is

demonstrated

that

the

summation form is in

agreement

with an

analytical

solution by Fredholm.

The Arrow oil

spill occurred on 4 February, 1970

and

during

the first

week

of March,

oil

was

observed

on

the

beaches

of Sable Island

some

120 miles Southeast of

the

spill

location.

Meteorological

data

in

the

form

of

reduced

geostrophic

winds have

been

published

by

Neu.

These

winds

were

utilized to

predict

the

oil

spill

trajectory

based

on:

(1)

a

surface velocity equal

to

3%

of

the wind

speed

and

aligned with

the wind direction,

and

(2)

a surface velocity

determined from

the convolution procedure

presented in

this

paper.

It

was found

that

the convolution

procedure

predictions

provided better

agreement

with

the

available information

relating

to

the

spill transport

to

Sable Island.

The

importance of an

adequate description of

prevailing surface currents

and

vertical

eddy

viscosity

is

illustrated.

Reviewer's Comments

This

model

has been reviewed

by

Stolzenbach,

et , al .

(1977)

who notes

that this is

purely

an

advection

model

since

it neglects spreading,

dispersion

and

other

processes

such

as

evaporation.

The model does

not

provide

for

inclu-

sion of coastline

boundaries;

therefore,

its

application

is

64



limited

to

far offshore

regions where wind induced

currents

dominate the movement

mechanisms.

The

model has been applied

to

the Arrow oil

spill (Nova Scotia) where,

after

calibration

via

the

eddy

viscosity parajneter

,

the measured

trajectory

was satisfactorily simulated.

65



Model

Name

or

Description

Narragansett Bay

(or Premack

and

Brown)

Model

Reference

Premack,

J.,

and

G.A.

Brown,

Prediction

of Oil Slick

Motions in

Narragansett Bay,

Proceedings

of

the

Joint

Conference

on

Prevention

and

Control

of

Oil

Spills

,

American

Petroleum Institute,

Washington,

D.C.

1973

Abstract

In

the

development

of

meaningful

oil spill

contingency

plans,

it

is

of

great value

in

establishing

the response

to

a

spill

emergency

to

have

predictions

of oil

slick

motions once

the

spill occurs.

In

an attempt

to

evaluate

some

of

the

present technical literature

on

oil spill

motion,

a

calculation

was made

for the oil spill

motion which

occurred

in

Narragansett Bay

in September,

1960,

when the tanker

P.W. Thirtle ran

aground

and

emitted

about

24,000

barrels of

Bunker

C oil

over

a

12 hour

period

before

the successful

abatement of

the

source

was completed.

The

existing

literature

on

oil

slick spreading

was

reviewed and the work

of

Fay

was chosen to

represent

the

slick's

spreading

characteristics.

The

existing

literature

on

the

oil

slick

drift was reviewed

and

the

work of Teason

, et

.

al

.

,

was

used

to

establish the drift

motion under

the

influence of current and wind

actions.

An available numerical

hydrodynamic model

of Narragansett

Bay

was used

to

calculate

the

current

characteristics in

the

vicinity

of the

spills

during

the

period

of

interest.

Appropriate wind

data were combined

with current data

in order

to

obtain

the

important

hydrodynamic

and meteoro-

logical

conditions. Since

no

comprehensive

theory

exists

at

the

moment

for oil

slick

spreading

and

drift,

a

simple

model

was

taken

in which

the

24,000

barrels were emitted

from

the

source in

the

form

of

12

hourly discharges

of

2000

barrels

each.

These individual

spills

were

then

handled

on

the

basis

of

the

available spreading

theory

and the

drift

motion

calculated

as

described

above.

Although

this is

a

crude

approximation,

it

does

give an

estimate of the

location

and

area

magnitude

of the

spreading

as a

function of

time after the spill.

The predicted

results were

compared

with

documentation

of

this

spill

as

presented

in

the

Providence

Journal

. The overall slick

motion

as

calculated by

this

procedure

was

in

good

agreement with

the

arrival

times

of the spill in

Newport

Harbor and

other places

in

Narragansett Bay and

with the

overall

surface

area

involved

66



in

the

spill.

This

example

of the

calculation

of the

oil

slick motion in an

estuary

at least

gives some

confidence

to

oil

spill

contingency planners

that

numerical

calculations

can be

made

for

use

in

planning

response and abatement

to

spills.

Reviewer's Comments

This

model has been reviewed by Stolzenbach,

et

.

al

,

,

(1977)

who

note that

this

model treats

advection

(both

wind and current) and

spreading.

Advection

due

to

wind

is

considered

to

be

directed at a

wind drift angle

of

20°

clockwise from the wind

vector.

The

modified

wind

induced motion

is

then

added

vectorially

to

the

tidal

currents

and both

are superimposed

on

the

slick

spreading.

Spreading

is

treated via

Fay's

(1971)

equations.

The

model

does treat

the

case

of

spills that

occur

with time

(as

contrasted

with

instantaneous spills).

This

is

accomplished via

a

uniform

discretization of

the

oil

spill

volume. However, the

resulting

subspills are

treated

independently

of

each other

via

simple

superposition.

That

is,

the

spill-spill interaction effect is

neglected.

The

model

has

been applied

in one case to

the

Thirtle

oil spill

where

some

limited

comparisons

have

been

made.

67



Model

Name

or

Description

Tetra Tech,

Incorporated

Reference

Wang,

S.

,

and

L.

Huang,

A

Niimerical

Model

for

Simulation

of Oil Spreading and Transport and

Its Application

for

Predicting

Oil

Slick Movement

in

Bays.

Tetra Tech, Inc.

,

Sponsored

by

U.S.

Coast Guard

Research

and Development Center.

Abstract

A

computer model

for

simulating

oil

spreading

and

transport

has

been developed. The model can be

utilized

as

a

useful

tool

in

providing advance information and

this

may guide

decisions

for

an

effective response

in

control

and

clean-up once an

accidental

spill occurs.

The

spreading

motion is simulated according to the

physical

properties

of

oil

and

its characteristics

at

the

air-oil-water

interfaces.

The

transport

movement is handled

by

superimposing

the

spreading

with

a

drift motion

caused

by

winds

and

tidal

currents.

By

considering

an

oil

slick as a

summation of many elementary

patches

and

applying

the

principal

of superposition,

the

model

is capable of

predicting

the

oil size,

shape,

and

movement as

a

function

of

time

after

a

spill originates.

Field

experiments

using either

cardboard

markers

or

soybean

oil

to simulate

a

spill

were conducted at

the

Long

Beach Harbor. Computer predictions

showed

good

agreement

with

the field

tracers. In

order to

accommodate

the

model in

local

port

offices,

two

hardware candidates are

proposed.

Reviewer's Comments

This model considers

the combined

effects of

advection

and spreading.

The numerical scheme

that is

employed is intended

to

simulate

the

simultaneous

effects of

advection,

spreading

and

dispersion.

Both

wind

and

tidal

current

advection are

considered.

The

differential

spatial effects

are

modeled by

use

of

elemental

cells. However,

the procedure

is

based

on a

linear

68



superposition

of

subspills

(in

the

spatial

sense) and the

effect

of

neighboring

subspills

is

not

considered.

In

other

words,

during

each

time

step

an

individual cellular

subspill is considered

to

react

independently of its

neighbors. This is considered

to be

a

serious

weakness

by

Stolzenbach ,

et .

al.(1977), who has reviewed

this

procedure

and who

also points

out

that

the

numerical

disper-

sion that results

from

this approach is not

directly

related

to

any

physical dispersion.

The

model considers

only

instantaneous

spills,

but, because of the fact

that

each cellular subspill

is

considered

to be new at the

beginning of each time

step,

there is no

reason,

in principle,

why time-dependent

spills

could not

be

considered.

The

model

is intended

for use

where

spreading

and advection are the

dominant processes.

Therefore, its

application

is limited

to mostly enclosed

water bodies

such

as

harbors

and

bays

and protected

near-shore

areas

having

relatively

short

time

and length

scales.

To

derive

maximum benefit,

it is

further

limited

to

those

situations

where

detailed

environmental

data

is

available.

The

model

has

been

field

tested

and

an

example

using

Long Beach harbor

(San

Pedro

Bay) is

illustrated.

Some five

different simulated

spills

using tracers

were

conducted

to

validate the

model.

A

computer code

is

included in the Appendix of the above

reference.

69



Model Name

or

Description

Council

on

Environmental

Quality (CEQ)

Reference

Stewart,

R.J.,

J

. W.

Devanney

,

III,

and

W.

Briggs

Section

III, Oil

Spill

Trajectory

Studies

for

Atlantic

Coast

and

Gulf

of Alaska, Primary,

Physical

Impacts of Offshore Petroleiim

Develop-

ment,

Massachusetts

Institute

of

Technology,

Sea Grant

Program,

MITSG

74-20,

Report

to

Council

on

Environmental

Quality, April, 1974

Abstract

Oil

spills

can

be transported

many miles

from

the

site of an accident

by

the

action

of

wind, waves

and

currents.

The

purpose of

this study is

to

obtain insight

into

the

likely

behavior

of

oil spill

trajectories

emanating

from

each

of the

thirteen

potential Atlantic

Outer

Continental Shelf (OCS) production

regions

and

each

of

the

nine

potential production areas

in the Gulf

of

Alaska

as

identified

by

the

U.S.

Geological

Survey.

In

addition, the likely behavior

of

oil spills

emanating

from

three potential nearshore

terminal

areas. Buzzards

Bay,

Delaware Bay and Charleston Harbor

are

examined

in

greater

detail.

Major emphasis

in all of

these

analyses

is placed

on the probability of

a

spill

coming

to

shore, the time

to

shore

and

in

the

case

of

the

terminal

(areas)

analyses,

the

wind conditions at the time the

spill first reaches

shore

Reviewer's Comments

This model

has

been

reviewed in

detail

by

Stolzenbach, et.al,

(1977).

It is

essentially

an

advection

model

with

two versions.

One version can be

applied

to

nearshore

areas

and

the

other

version

is

intended

for

application

to offshore

areas.

Advection by

wind,

tidal

currents

and

'residual'

currents are

considered.

Application

of the model

requires

a

knowledge

of

the

tidal

currents

,

residual currents

(in the case

of

the

offshore

version)

and

wind

measurements

appropriate

for the

region

under

study.

70



Model Name

or

Description

Batelle

Oil Spill Transport

Model

(BOSTM)

Reference

Ahlstrom,

S.W., A

Mathematical

Model

for

Predicting the Transport of Oil Slicks in

Marine

Waters,

Batelle

Pacific

Northwest

Laboratories, Richland, Washington,

1975

Abstract

(not

available)

Reviewer's Com.ments

This model has been reviewed by Stolzenbach,

et

.

al

.

(1977)

and numerous references

to

it

appear

in the

open literature.

From these reviews

and

citations,

it

appears

that the

model

treats advection,

spreading and

dispersion

but

does

not

treat

weathering. The CAES

model

appears to

be

based

on

the BOSTM model with the

addition

of weathering

so

that the CAES

comments

also apply to

the

BOSTM

model.

Inherent in the Discrete Parcel

Random

Walk

method is

the

assumption that each parcel

(subspill)

behaves

independently

of

the other parcels.

Stolzenbach,

et.al.

(1977)

points

out

that this assumption

has

not

been

proven

and that

it gives

rise to

a

numerical

dispersion

which

may

not

be

realistic.

Moreover,

the

model employs

some

arbitrary

empirical

factors

whose origin

is

uncertain

,

71



Model Name or

Description

U.S.

Coast

Guard (New

York

Bight)

Reference

Miller,

M.C.,

J.C.

Bacon

and

I.M,

Lissauer,

A

Computer Simulation

Technique

for

Oil

Spills

Off the New

Jersey-Delaware

Coastline

,

DOT

U.S. Coast Guard, Washington, D.C.

1975

Abstract

Predictions

for

the

movement of

oil slicks

and their

impact

implications

along

the

shoreline of

New

Jersey and Delaware were determined for two

potential

deepwater

ports

and

two

potential drilling

sites.

A

hydro-

dynamic numerical model for

the New York

Bight

area

was

coupled

with

a

wind generating model

to

produce

temporal

patterns

of

concentration of oil.

Shoreline

impact

determinations were made for the four

spill

sites

for

the

average

winter

storm

conditions and

average

summer

high

pressure

systems generated by

the model.

Reviewer's Comments

This

model

has

been

reviewed by

Stolzenbach,

et

.

al

.

(

1977)

,

who

points out that

many

details

are

lacking

in

the

report.

The

model

consists

of

essentially

a

numerical

hydrodynamic

system

which utilizes

a

wind field generating

submodel

to

predict fluid

particle

velocities. The

latter,

in

turn,

are

employed

to

yield

the

oil

spill trajectories.

72



Model Name or Description

Delaware

Bay

(Wang, Campbell,

Ditmars) Model

Reference

Wang, H.,

J .

R.

Campbe]

1

,

and

J.D.

Ditmars,

Computer

Modelling of

Oil Drift

and Spreading

in Delaware

Bay

,

CMS-RANN-1-76 ,

Ocean

Engineering

Report No.

5,

University

of

Delaware,

Newark,

Delaware,

1976

Abstract

A

generalized

two-dimensional model and an

interactive

computer code

for

the

determination of

the

oil

slick dispersion

are presented.

The model

considers

two

mechanisms

to

dominate,

spreading

and

dispersion.

Drifting

refers

to

the

drift

of

the

center

of

mass

of

the

slick

and

is influenced by winds,

water

currents and

the

earth's

rotation (Coriolis

force).

Spreading

refers

to

the

spread

of the

oil slick

with respect to

its center

of

mass

and a function of

first,

a

gravitational force;

second,

a

viscous

force;

third,

a

diffusion process.

Relevant

details

and

user options

of

the

computer code

are

discussed. An important adjunct

of

the computer

code

is

the capability

for interactive

graphics.

This paper

concludes

with

a

comparison

between this

model

and

field

data taken in Delaware Bay.

Reviewer's

Comments

This

model

has been reviewed by

Stolzenbach,

et.al.

(1977)

who

notes that this

is

the only model

that

includes the effect of

advection

due

to

waves.

The model

treats advection

due

to

wind

and

current also, as

well

as

spreading

dispersion. Spreading is treated

by

using

a

modified

approach

to

Fay's

(1971)

equations.

The first

two

phases (gravity-inertia

and

gravity-viscous)

are

treated

unchanged.

However, in lieu of the

third phase

(viscous-surface tension),

the

modellers substitute a

73



Fickian diffusion

relation

which

requires

evaluation

of

a

dispersion

coefficient.

The

authors

state that the reason

for

this

substitution

lies

in

the

fact that

while the

third

phase

exists in the

case

of

small

scale laboratory-

experiments, its

existence is questionable in the

proto-

type

(or

field) experiments. Therefore,

the influence

of

dispersion

completely dominates

behavior beyond the

second

phase.

The

model results

have been compared

with

some field tests

of

drifting

as

carried

out

in

Delaware

Bay

74



Model Name

or Description

U.S.

Coast Guard

(New

York Harbor)

Reference

(a)

Lissauer, J.M.,

A

Technique

for Predicting

the

Movement

of

Oil

Spills

in

New

York Harbor,

U.

S.

Coast

Guard

Research

and

Development

Center,

Groton

, Connecticut

(1974)

(b) Kollmeyer, R.C.

,

and

M.E. Thompson

,

New York

Harbor

Oil

Drift Prediction

Model,

Proceedings

of the

Joint

Conference

on

Prevention and

Control

of

Oil Spills, American

Petroleum

Institute,

Environmental Protection Agency,

and

U.

S.

Coast

Guard,

Washington, D.C.

(1977)

Abstract

(Reference (b))

An

operational predictive

oil

slick

movement

model

is

developed

and

applied to

New York Harbor.

This

computer simulation

employs

hourly

tidal currents for

all

stages

of

the tide as input

data,

combined

with river flow

and

continuous

wind data

to

predict

oil

slick

movement.

Slick

spreading

and

transport

is

accomplished using

a

conservative form

of

the dif

fusion/advection

equation.

The

shape of the

slick

as

well

as

its

possible

separation

into multiple

slicks

due

to

current divergence

is

predicted.

Time

steps

on

the

order

of

three

minutes

and

grid spacing

of

200 meters

allow

short

term,

small scale

slick

position and shape

predictions

xo

facilitate

quick

response

for location

of sites

for

containment

or

cleanup

activities.

Hindcasting features

allow for

possible

source location

of

the

initial

spill.

Reviewer's

Comments

Reference (a) has been reviewed by

Stolzenbach,

et.al.

(1977).

Reference

(b) is

an update

and

an

enhance-

ment

of the

work

begun

by

Lissauer

(1974).

Advection

is

by

wind,

tidal

currents

and

fresh

water

inflows

from

the

Hudson River. In

reference

(a),

spreading

followed

Fay's

(1971)

model. However, in

reference (b),

spreading

75



follows

Murray's

(1972)

turbulent

diffusion

approach.

Both approaches require

a

moderate

amount

of field

data

under

a

variety

of

conditions

in

order

to

calibrate

the

model.

Stolzenbach,

et.al.

(1977)

notes

that although

the

model

can

be

applied

to

other

harbors,

estuaries

and

bays, its

usefulness is hampered by the

data require-

ments including

knowledge of the fresh water

inflows.

He

also

points

out that the

accuracy

drops off in areas

close to

shore.

As reported

in

reference

(b),

the

model

has

been

extensively

calibrated by a

physical model

(U.S. Waterways Experiment Station,

Vicksburg, Mississippi)

and

by

numerous

observations

in New York

Harbor.

Both

the

time

step

interval and grid size appear

to

be

small

enough

to

minimize

numerical

errors

but

error

analysis

has

not

been

conducted.

76



Model Name

or

Description

use/API

Reference

(a)

Kolpack,

R.L.,

N.B. Plutchak and R.W.

Stearns,

Fate of Oil in

a

Vfater Environment, Phase

II

-

A Dynamic

Model of

the

Mass

Balance for Released

Oil

,

Chapter

19,

Settling

,

American

Petroleum

Institute,

Publication

No. 4313,

Washington, D.C,

1977.

(b)

API,

Publication No,

4212

(c)

API,

Publication No.

4213

(The

above

publications

are

out-of-stock)

Abstract

(not available)

Reviewer's

Comments

This

model

has been reviewed by

Stolzenbach,

et.al.

(1977).

It

is

known

that

the

model

includes

advection, spreading

and weathering with

particular

attention

on

the

weathering

processes.

77



Model

Name

or

Description

SLIKFORCAST

(with

OILSIM

and SLIKTRAK)

Reference

(a)

Audunson,

T.,

V.

Dalen

,

J. P.

Mathisen,

J.

Haldorsen

and F.

Krogh ,

SLIKFORCAST

-

A

Simulation

Program

for Oil

Spill

Emergency

Tracking

and

Long

Term

Contingency

Planning,

Exploration

and

Production

Forum,

London,

England,

1980

(b)

Det

Norske

Veritas,

et.al.,

OILSIM

-

Oil Spill

Simulation

Model Phase 1

,

Veritas

Report No.

77-441

Det Norske

Veritas Research

Division,

Norway, 1977

(c) Blaikley,

D.R.,

G.F.L. Dietzel,

A.

W,

Glass,

and

P.J.

Vankleef,

SLIKTRAK

-

A

Computer Simulation

of

Offshore Oil

Spills, Cleanup,

Effects and

Associated

Costs,

Proceedings of

the

1977 Oil

Spill

Conference

,

American

Petroleum Institute,

Environmental

Protection Agency

and U.S. Coast Guard,

1977

Summary

(Reference

(a))

The

oil spill simulation program Slikforcast is

an

integrated program

system

where

the

main components

are

a

deterministic oil

spill simulation

program,

a

statistical

oil spill simulation program.,

a

hydrodynamical model for

tidal currents,

a da,ta preprocessor, and various

output

routines.

Wind

data and data on residual currents

must

be

supplied

from outside

sources.

The wind

data

may

be from

(i) meteorological

wind models

with winds on a

gridded

net;

(ii) from

time

series

of

wind

from

one

or

several

observational

stations;

(iii) from statistical

wind

data

from

given

locations.

The

data

preprocessor is used to

arrange

the

data on

a

unified

format suitable

for

the

simulation models.

Simulation

of

oil

spill

drift and fate

may

be

carried

out

using either

the

deterministic

or

statistical

model or

using

the two simulation

models in

a

coupled

mode.

In

the

latter

case,

the

results from the

deterministic

simulations are

used

as

starting

conditions

for

the

statistical

model.

This permits oil

spill forecasting

both on

a

short

term and

long

term basis.

The

deterministic

model is

interactive

allowing

for

continuous

updating

of

the

simulation

results

against

field

observations.

78



trajectory

analysis.

Reference

(c)

is

the subroutine

that

deals

with the

statistical

trajectory

analysis. This

is

a

general oil spill

simulation

program designed

specifically

for

accidents (particularly blowouts)

in

the

North

Sea

but it

is

intended

for

application

to

different

geological

areas.

It

simulates wind from measurements

or from

historical

data.

It

also

simulates

dispersion

into the water column

and

evaporation

but

does

not simulate biodegradation

and

photooxidation because these are

very

slow

relative

to

other

phases.

This

oil

spill

simulation model

is

not

designed

for

and not

sufficiently

accurate for

detailed coastal effect

evaluation.

However,

both

short term

deterministic and

long term probabalistic

oil

spill forecasts

are

possible.

80



Model

Name or Description

MOST

Reference

Paily,

P.P.

,

and

B.N.

Rao,

MOST-The

Model

for

Oil Spill

Transport,

Hazelton Environmental

Laboratory,

Northbrook,

Illinois, 1978

Abstract

(not

available)

Reviewer's

Comments

This model treats advection,

spreading and

dispersion

but

no weathering. Both wind drift and

surface currents

are

apparently

treated.

Spreading

is treated by Fay's

(1971)

approach

combined with

diffusion.

The

model

has

been

applied

to

the

BRAVO

blowout

(North

Sea) but apparently overestimated

the

slick size.



Model

Name or Description

Deepwater

Ports

Project

Office (DPPO)

Model

(LOOP,

Inc.,

and SEADOCK,

Inc.)

Also

referred

to as SEADOCK Model

References

(a)

Williams,

G.N., R.

Hann

and W.P.

James,

Predicting

the

Fate of Oil in the

Marine

Environment,

Proceedings

of the Joint

Conferen

-

^e

on

Prevention

and

Control

of

Oil Spill

s

held in

San Francisco, California.

American

Petroleum

Institute, Washington,

D.C.,

1975.

(b)

SEADOCK

Deepwater

Port Final

Environmental

Impact Statement

,

Volume

III.

Prepared

by

Arthur

D.

Little,

Inc.,

Cambridge,

Massachusetts,

(c)

LOOP Deepwater Port License

Application

,

Volume

I.

Prepared by Arthur D. Little, Inc.

Cambridge, Massachusetts.

(d)

Carver, D.R.

and

G.N.

Williams, Advancement

in

Oil

Spill Trajectory

Modelling, Proceedings

of Oceans

'78

,

Marine Technology Society,

Washington,

D.C.,

1978,

Abstract

The

continuing increase

in

offshore crude

oil

production

and transportation is presently coupled with

widespread

concern

over

protection

of

the environment.

This

has

led

to

interest by members

of

the

petrochemical

community

in the

development of suitable

m.ethods

for

quickly predicting

the

probable

transport path and coastal

impact time

of

a

possible

oil

spill

in

the offshore

environment.

An oil slick

simulator

of

the

stochastic

trajectory type has

been

enhanced

in

an

effort to

provide such methods.

In

particular, four

areas

will be

addressed.

First , both the Fay radial

spreading equations

and

a

long-

term dispersive

algorithm

are

now provided.

Additionally,

the slick

may

now

assume an elliptical

shape.

Secondly,

wind

and current

forcing

functions

may now be

generated

with

the use

of

Markov state

transition

matrices as

well as

through

the

use

of

input tim.e

histories.

Thirdly,

the

model

will

adaptively calculate

coefficients

for

the transport

equations

in

an

attempt

to

correct for

deficiencies

in

the

particular

equations

used.

Finally, the model

will now

execute

in

a

real-time

m,ode

with

an on-line

computer

terminal to

allow

tracking to

occur during

an actual

spill.

82



Reviewer's Comments

Stolzenbach,

et .

al

.

(1977)

reviewed

reference

(a)

above

which

is referred

to as

the SEADOCK model as

well

as

predecessor

reports

to

references

(b)

and

(c)

which

he

refers

to as

the DPPO

model.

Actually, all

four

references taken

together constitute

a

continuing effort to

predict

the

probable

transport

path

and coastal

impact time of an oil

spill

occurring

in

the

offshore

region. Reference

(d)

describes

the

most recent enhancements

to

this

model

but

unfortunately, many

of

the details are not

provided.

There-

fore, some details are assumed

to be

similar

to

those

reported

in

references

(a),

(b)

and (c).

The

m.odel

objectives

dictated

the

need

to

follow

a

probabalistic

approach,

but

the

model

incorporates various

levels

of deterministic

elements.

In

addition, an option

exists

for

operating

the model

in a

deterministic

mode.

The Fay

(1971)

equations are

used

for modeling spreading

and advection

is modeled for

both wind

and

current

by

using

the

available data

for the region. Garver and Williams

state

that

although the

vector

combination approach

to

slick

advection is

poorly supported, the

behavior

of

actual

oil

spills

does

not

justify

the use

of a

more

rigorous

modeling

method.

They

do,

however,

use

a

weighted

average

approach

to

evaluate

the

proportionality

constants and provision is

made

to

incorporate

new

values

as

more data

becomes available.

83



An

algorithm

for

modeling

long-term

dispersion

is

provided.

This

algorithm is

based

on

a

very limited

number

of observations

but

does

permit

the slick

to

assume

an

elliptic

shape.

In

addition,

the

subsurface transport

processes are

modeled.

The

movement

of

the slick

is

tracked

for

a

specified

duration

of

time

via

employment

of actual

data

(if measured) or of simulated

data (based on

a

Markov

chain model)

if

data

is not

available.

Thus,

the model

is

suitable

for

both

environmental assessment

and

planning

studies

as

well

as

for operational purposes

during

emergencies and

clean-up.

The

latter is

known

as

the

adaptive tracking feature.

Certain submodels that

account

for

weathering

and

degradation

of the

slick

are also

included.

These

follow

the

first

order model

of

Moore,

Dwyer

and

Katz

(1973)

for

evaporation

and dissolution

and arbitrary

empirical functions

for emulsif

ication and

sedimentation.

In

summary,

this

model represents a

very

comprehensive

approach

to

the

problem

of

predicting oil

spill

trajectories

in the offshore

region and even

though

many

of

the

submodels

are

elementary,

the

fundamental

stochastic

approach

is

will

justified.

84



Ocean currents were

simulated by

averaging estimates

obtained

from

a

long-term

study of

surface drifter

returns.

The

model envisions

that

detail

information from

ocean

surface

transport

or

continental

shelf

circulation

studies

will

be available

as input. Advection is

then

simulated

by

the

vectorial addition

of

ocean and wind-induced currents

Evaporation

is

simulated by

application

of

a

numerical

solution

to

the procedures

developed

by

Wang, Yang and

Hwang

(1976).

The

subsurface transport

of the

dispersed

oil

is simulated by a

three-dimensional

mass transport equation

which

is solved

by a

quasi Monte Carlo technique.

Although it

is

stated

that extensive model

testing

was

performed

in

order

to

assure

that

the

sub-process

models

correctly

interfaced

with

one

another,

it appears

that

the

model

contains

a

mixture

of

numerical as

well

as

physical

dispersion

.

The

model

has been applied

to

four

different

versions of

a

simulated

spill.

Unfortunately,

there

are

no

comparisons

with

field

observations.

86



Model

Name or

Description

Puget

Sound Model

Reference

Karpen

,

J.

,

and

J.

Gait,

Modeling

of

Oil

Migration in

Puget

Sound, Proceedings

of

Oceans

'

79

,

Marine

Technology

Society,

Washington, D. C.

Abstract

The

oil

migration is simulated

with

a

mixed

Lagrangian-Eulerian model. The

movement

of the

oil is

modeled

with Lagrangian point masses

or

Lagrangian elements

(LE).

Time

dependent dispersion is applied

to

the

individual

LE

' s

.

Eulerian

current

and wind fields

are

used

to

advect

the LE

'

s

Several scenarios for

hypothetical

spills in the

Straits

and

upper

Puget Sound are shown. The model

accurate-

ly

predicted the

migration of the diesel oil

spill

at

Ancortes,

Washington.

The

model

is

general enough

so

that

submodels

from currents and

winds developed

for

other regions can

be easily

integrated into

the

simulation.

Reviewers

Comments

A

model

najned

the Puget Sound Model

was

reviewed

by

Stolzenbach,

et

.

al

(1977),

but the model described

in

the

above

reference is an entirely

different

one

than that

reviewed

by

Stolzenbach. The

model

simulates

advection

and

the

combined effects

of

spreading

and

dispersion.

Spreading,

using

the theoretical approach

developed

by

Fay

(1971)

was

not

employed. Instead the

available data

was

used

to determine

a.

spill

length scale

as

a

function

of

time.

The

spill length corresponding

to

the

spill size

was then

used in

a

modified random

walk scheme

to simulate

87



the

combined

spreading

and dispersion.

It

is

stated that

this approach

is

comparable to

diffusion

by continuous

movements for

discrete

particles or

Fickian

diffusion.

The

advection

for

wind

and

tidal

currents

are

then

super-

imposed on

the

combined

spreading

and

dispersion.

Most of

the

data

used in

the regression

equations

to

determine

the

spill length, size and

time

relations do

not

consider

spill

rates.

There is some

question

how

this technique

can

be used in

situations

where

spill

rate

is

an

important

factor.

Also,

there

may be

other

factors (i.e., boundary

conditions)

that

effect

the

spill length-time relationship.

88



Model Name or

Description

Canadian

Arctic

Environment Service (CAES

Reference

Venkatesh

,

S.,

S.H.

Sahota

and

A.S.

Rizkalla,

Prediction

of

the

Motion

of Oil

Spills

in

Canadian Arctic Waters,

Proceedings

of

the

1979 Oil Spill Conference, Los

Angeles,

California,

American Petroleum

Institute,

Environmental Protection Agency,

and

U.S. Coast

Guard

(1979)

Abstract

An

oil

spill movement

prediction

m.odel

operating

as

part

of

a

real-time Environmental

Prediction Support

System

for the

Canadian Beaufort

Sea

has

been

developed.

The

present

version

of

the model considers

spills

only in

open waters,

that is,

the

sea

surface

is considered to

be

ice

free. The

model has been

partially

verified with

data

obtained from oil

simulation

experiments

conducted

in

the

Bay

of

Fundy

,

off

the coast

of Canada

during

the

months of

August

and September 1978.

With

the

use

of

observed

winds, the

model-predicted

locations

of

Orion

buoys used

to simulate the motion

of

oil on

water,

agreed

fairly

well with their

observed

locations.

These

verifi-

cation

tests also

pointed

out

the

need

for

high

resolution

surface

wind

forecasts

—

essential

data

for

computing

wind-

driven

water

currents

which

move

the

oil.

Reviewer's

Comments

This

model uses the

numerical

technique

known

as the Discrete Parcel

Random

Walk

method.

This method

is identical

to

that

used

by

Ahlstrom

(1975).

In a

sense,

this

model

is an

adaptation

of

Ahlstrom'

s

model

(BOSTM)

.

Spreading

follows Fay's theory. Of

the

weathering

processes

only

evaporation

and

emulsif

ication are

considered because

of

their

predominance

in the

first few days

of

slick

formation.

Treatment

of both

evaporation and

emulsification

89



follows

the procedures

developed by

Mackay

and

Leinonen

(1977).

Advection is considered

to

be

due only

to

wind-

induced

surface

currents

and

is

based on the

work

of

Madsen

(1977).

The

expression

for

steady

surface

drift

becomes a very

simple

relation.

The computational method

assumes

that

the sub-

spills

act

independently of each other.

Therefore, the

effect

of

neighboring

subspills

is

neglected

as

is

the

spill-spill interaction effect.

The

model has been

applied

to

four

separate simulation experiments conducted

in

the

Bay

of

Fundy.

90



Model

Name

or

Description

Riverspill

Reference

Tsahalis,

D.T.,

Contingency Planning

for

Oil Spills:

Riverspill

-

A

River Simulation-

Model,

Proceedings, 1979 Oil Spill

Conference

,

Los

Angeles,

California,

American

Petroleiim

Institute, Environmental Protection

Agency,

and

United

States Coast

Guard

(1979)

Abstract

A simulation

model,

Riverspill, has been

developed for the

prediction

of

transport, spreading,

and

associated land

contamination

of

oil spills on

rivers. The

effects

of

volume

and

type

of oil,

use

of

Oil

Herder

or

not, type, location, and time

of

occurrence

of

the oil

spill,

geometry,

and hydrographic characteristics

of

the river and

wind speed and

direction are taken

into

account.

The model

is

capable

of operating in either deterministic

or

stochastic

mode.

When

the model

is used

in

the

deterministic mode, it

predicts

the path

and associated land contamination of

a

specific

oil spill

as

a

function of

time.

When

the

model

is

used in the

stochastic

mode,

it estimates the

probability

that

an oil

spill

will be

transported

into

a

specific

region

after

an

accidental

discharge

within another

specified

region. In

the

present study,

the

model

is specifically

applied

to

the

lower

Mississippi

River.

However,

the model

is

general

and can

be

applied

to any river.

The predictions

of the

model

are

in

very

good

agreement

with the observed

behavior

of

actual oil

spills on

the Mississippi

River.

Reviewer's

Comments

This

model was developed specifically

for

river

flows.

Spreading

follows

Fay's

(1971)

theory,

in

which all

three

regimes

are

modeled.

Advection

due

to

wind

and

current

is modeled

by some

derived

relationships

which depend

on

the

direction

of

the

wind

velocity vector

relative to the

current

vector.

Some experimentally

d9termined coefficients

91



are

employed in the

derived relationships.

Cross

flows

(i.e.

,

secondary) are

also

considered.

The

model

has

been

applied to

two

accidents on

the Mississippi River. The

agreement

between observed

and

model

predicted

deposition

sites

ranged

from good to excellent.

92



Model Name

or

Description

National

V/eather Service

(NWS

)

Model

References

(a)

Hess, K.W.,

The

National Weather

Service

Oil

Spill

Motion

Forecasting Program, Workshop

on

the

Physical Behavior

of Oil

in the

Marine

Environment

,

Princeton,

University,

Princeton,

New

Jersey,

May

8-9,

1979

(b)

Hess, K.W.

,

and

C.L. Kerr,

A Model

to

Forecast

the Motion

of

Oil

on the Sea,

Proceedings of the

1979 Oil

Spill Conference

,

Los Angeles,

California.

American

Petroleum

Institute,

Environmental

Protection

Agency

and

U.S. Coast Guard,

Washington,

D.C.

1979

Abstract

(From

Reference

(a)

Text)

The

purpose of

this

model is

to

provide

an

operational method

to forecast the movement

of

oil

spilled

in

the ocean. The

model

utilizes the

National

Weather

Service (NV/S)

meteorological forecasting

capabilities

to

provide

scientific prediction

of the mediiim

or

long-range

(up

to

5 days) future oil

behavior.

In

this time

range,

oil

motions

are strongly influenced, if

not

dominated,

by

wind

effects

(wind

stress, wind-driven

ocean

currents,

wind

waves

and

evaporation). Forecasting

using

numerical

models

of the

atmosphere

give

better

results

for this

time

range

than the

use

of either

a

statistical

(climatology)

or

a

presistence

approach.

The

present model

does

not

use

the

trajectory

and

point-mass

simplifications

of

oil

behavior; instead

a

two-dimensional

approach

is

employed

to

predict the

spatial variation

of oil thicknesses.

The

oil

spill model

consists of three

major

segments,

relies heavily on

finite

difference

techniques

and

is

driven

by

output

of

NWS

atmospheric

models. The

three separate parts

are:

(1)

a

model

of

the

atmospheres near-surface planetary boundary

layer,

(2)

a

dynamic

model of

the upper

mixed-layer of

the

ocean,

giving

surface

currents, and

(3)

a

dynamic

model of

two-dimensional

variable thickness

oil

distribution

on the

sea. In

general,

the

lirst

two

segments

provide

input to

the third

in the form

of stresses at

the upper

and

lower

oil

boundaries.

The

most important

simplifications of the

present

model are

neglect

of

tide and

wave effects

and

absence

of

weathering.

Reference

(b) provides

additional

details

on this

model which

is

under continuing

development.

93



Abstract

(From Reference

(b))

A model

to forecast

the motion

of

oil spilled

on

the

surface

of water was

established

by

combining

separate

models for the

motion

of oil, the

motion of

water,

and

the

motion

of

air.

The model

for

the

motion

of

oil

is

based

upon

the

hydrodynamic

equations

as

they

apply

to

oil

on

water. This

model

requires

information

at both

the

lower

and

upper

boundaries

of

oil. At the

oil lower

boundary, the

information is obtained from

a

model

for the motion

of

water.

This

model is formulated

by combining

Ekman

dynamics

and continuity for the

upper

mixed

layer of the

sea.

At

the oil upper

boundary,

a

model

for

the

motion

of air

provides

the

required

information. This

model is

based upon an analysis of

output obtained from

one of

the National

Weather

Service's

multi-level

atmospheric models. A number of case

studies

demonstrate

the

features of

the

separate models

and

the

composite

oil

spill

model.

Reviewer's

Comments

This

is a very comprehensive

model

which

takes

advantage

of

the

operational wind

forecasts

made

available

by

the National Weather Service.

Separate

models

for

the

motion

of

oil , water and

air are

combined

into

a

composite

model

which is undergoing continuing

development and

improvement

.

The

model

has

been

applied in

preliminary

form to

the

Argo Merchant

spill.

The

model

results in

com.parison with observations

indicate

the

potential

applications and limitations of

this model.

The

model

approach appears

well suited

for

making real

time

fore-

casts

of

oil motion

in

locations far offshore

and

especially

where

wind is the dominant

driving force.

94



Model

Name

or

Description

U.S. Coast Guard

(Long Island Sound)

Reference

Kollmeyer,

R,C.

,

Long

Island

Oil Spill

Drift

Prediction Model,

Proceedings

of

Workship on

Government

Oil Spill

Modeling

,

November

7-9,1979

Wallops

Island,

Virginia,

NOAA

,

Washington,

D.C.

February

1980

Abstract

Because

of the sensitive

nature

of the

Long

Island

area

and

the complex

nature of the surface

currents in

the

Sound, the

On-Scene

Coordinator

(OSC) must

be

able

to

predict

oil

spill

trajectories accurately in

order

to

deploy

cleanup

equipment

and

to

protect sensitive

areas.

Present

oil

spill

movement

prediction

models are inadequate

for

this

need and

are not

readily

accessible

to

the OSC.

The

goal

of

the

project

is the production

of

a

reaH;ime

prediction

model that will forecast

the movement

and

spread

of an

oil

spill in Long

Island

Sound.

Upon

command,

the

model

will,

for

a

given

period,

produce

a

time

series of

charts

displaying the

location,

shape

and

concentrations

of the oil spill.

The

model

will be constructed

on

the

computer

facilities

provided

by

the

Department

of

Computer

Science,

U.S.

Coast Guard

Academy.

Captain

R.C. Kollmeyer

will be

the

overall project coordinator.

A close

liaison will

be

maintained

am.ong all

interested

and contributing units.

At

present, the

following

Coast Guard

units

are

involved:

1.

Coast

Guard

Academy

2. Commander,

CG Group, Long Island Sound

3. USCG

Research

and

Development Center, and

4.

USCG

Oceanographic

Unit.

The

oil

drift mechanisms

to

be

modeled

will

include

the

following:

1.

predicted

tidal

currents,

2.

Stokes

drift,

considering

both

duration and

fetch

limitations

3.

leeway

of

oil slick

caused by

the

wind,

and

4.

wind

drift currents

of

the

surface

layer.

95



A

relatively

sophisticated computer

graphics

output is desired in

the

form

of

segment

maps

showing

the

spill,

its

location,

areal size,

and

concentration

gradients. These

maps

would

be

produced on

a

time

basis,

showing the

oil

spill's

predicted

location

every 15

minutes

from the time of

th^

sDill.

The

preparation

of the

tidal current

data

set

will

include

the

use

of

overlays for the

NOS

tidal current

charts

to

allow

their transfer

to

tho model matrix. A scaling

program (inverted

smoothing)

will then determine the

currents

for

all other

points on the matrix for

each

of the 13 current

charts available. Currents

along

the

shore

boundaries will

be

made zero unless

other

information

is

available.

A planned

program of

verification and

testing

will

be

developed

at

part

of the

mod^^l

completion.

Proce-

dures

will be proposed by

which small

oil

spills in

Long

Island

Sound

may

be

monitored

and

used

in

a

hindcast

mode.

In

addition,

a

testing

program

will

be

drafted

that

would use oil

drift

simulators

which

can

be

tracked

and

compared with

model

predictions.

Reviewer's

Comments

The

above

reference simply

describes a program

being

undertaken

to

develop

a

model

with certain

specific

goals

and features.

It

likely

will be

similar to

the

model

developed by USCG

for

New

York

Harbor.

96



Model Name

or

Description

SPILSIM

References

(a)

Pickett,

R.L.,

A

Surface

Oil

Spill

Model

for

the Great

Lakes

, Proceedings of

the V/orkshop

on

Government

Oil

Spill

Modeling

,

November 7-9,

1979,

Wallops Island,

Virginia

NOAA,

February

1980

(b)

Boyd,

J.

D.

, A Surface Spill

Model

for the

Great Lakes,

Great

Lalces

Environmental Research

Laboratory,

Ann

Arbor,

Michigan, 1979

Abstract

(Edited from Reference

(a))

This

model was

developed

as an

operational

forecast

model

for

the

movement of surface-pollutant

spills

on

the

Great Lakes

with

special

emphasis

on

oil

spills.

Oil

spills

are

of particular

concern

because

of

their

environ-

mental

impact

and

the

substantia.l quantities

of

oil

transported

on the Great Lakes,

both

as

cargo

and

as

fuel. The Great

Lakes

Environmental

Research

Laboratory (GLERL)

undertook

this

modeling

effort

because

a

number

of

models

were

being

developed

for

oceanic spills

but none

were

being

developed

for

those on

the

Great Lakes. The

resulting model,

SPILSIM,

is

a

batch

oriented

model

derived form

oil

spill models

from

the Canada

Center

for

Inland

Waters

(CCIW)

and

NOAA's Pacific

Marine

Environmental

Laboratory (PMEL)

. It

predicts

the movement

of

an insoluble

surface spill anywhere

within

the Great

Lakes,

given spill

size

and location and surface

currents

and

winds

in

the

area of

interest. Modifications

to

make

the model interactive

are straightforward.

Reviewer's

Comments

This is

a simple

model

that

simulates

advection

by

wind

and

currents.

97



Model

Name

or

Description

Reference

Environmental

Data

and

Information

Service

(EDIS)

Model

Bishop,

J.M.

,

A

Climatological

Oil

Spill

Planning

Guide,

No.

1,

The New York

Bight

.

NOAA,

Washington,

D.C., 1980

Abstract

Over the

past

4

years, the Environmental Data

and Information

Service (EDIS) of NOAA has developed

a

multiple trajectory

oil

spill

model. The

model is

based

on the

archived

wind

and current

data available

within

EDIS's

National Climate

Center

(NCC)

and National

Oceanographic Data

Center

(NODC).

The

model was

originally

designed for assessment of

possible

environ-

mental

impact due to

construction

of

a

deepwater port

off

the

Texas

coast, but

has

been used

effectively in

the

Argo

Merchant

and

Compeche oil

spills

for a

rapid

estimate of

the

impact

areas.

The successful

use

of

this model

for

climatological

assessments of large

ocean

spills

leads

to

the

conclusion

that

this type

of

climatological

forecasting

technique should

be

a

part

of

our overall response

to

major oil

spills.

Although

the

utility

of

this

approach

has

been

shown

in

these

two examples of

large

open-ocean

oil spills,

a

better application

of

this

climatological

(Type

I) model

is

in

contingency

planning

(prespill

resource allocation).

In

this

mode,

one

can map

most probable

imnact zones

over

known

local

resources

(biological

or

economic).

Such

a

use has

been

initiated

in

a

recent

EDIS

publication

produced for

use by

the

3d

Coast Guard

District

contingency

planners,

couples

key environmental data

(both

physical

and

biological) with climatological oil

spill trajectory

forecasts.

Reviewer

'

s

Comments

This

model is an

enhancement

of

the

DPPO

model

but

in an

empirical

-simplified

direction

rather

than

in

the

fundamental-comprehensive

direction

taken by

Garver

98



and

Williams

(1978).

Advecticn

due to

wind and current is

determined using measured

data.

These,

in

turn, are coupled

with

Fay's

spreading

theory to

predict

the

spill

trajectories

99



Model Name

or

Description

Particle-In-Cell

(PIC)

Model

Reference

Tingle,

A.G.,

Perturbation Analysis

of

the

New

York Bight,

Proceedings

of the

Workshop

on

Government

Oil

Spill

Modeling,

November

7-9,

1979, V/allops

Island,

Virginia,

NOAA,

Washington, D.C.,

February

1980.

Abstract

The

physical

transport of

pollutants,

their

modification

by

the

coastal

food

web,

and transfer

to

men

are

problems

of

increasing

complexity

on

the

continental

shelf. In an

attempt

to

separate

cause and effect, a

computer

modeling

technique

is

applied

to

problems

involving

the

transport

of

pollutants

as

one tool in

assessment

of

real

or potential

coastal perturbations.

Approaches for

further

model

development of the

biological response

within

the

coastal marine ecosystem

are

discussed. Our

present

perturbation

analyses

consist of

1)

a

circulation

submodel,

2)

a

simulated

trajectory

of a

pollutant

particle

within

the

flow field,

and

3)

a

time-dependent wind input

for

each

case

of

the

model.

The

circulation

model

is

a

depth-

integrated,

free

surface formulation

that

responds to

wind

stress, bottom

friction,

the

geostrophic pressure

gradient,

the

coriolis

force,

and the bottom topography. The

transport

diffusion model

is

based

on

Lagrangian

mass

points,

or

particles

moving

through

a

Eulerian

grid.

The

trajectories

of material

moving on the

surface

and

in

the

water

column

are

computed. It

has

the

advantage

that the history

of

each

is known. With these

models, we have

been able

successfully

to:

1)

reproduce drift

card data

for

determining

the

probabilities of

a

winter

oil spill

beaching

within

the

New

York

Bight,

2)

analyze the source

of

floatables

encountered on the

south

shore of

Long Island

in

June

1976,

and

3)

predict the trajectory

of oil

spilled

in

the

Hudson

River

after

it had entered the

New

York

Bight

Apex.

For

future

analyses,

the

shallow

water

model

can

be

modified

or replaced

with

a

numerical

model that

contains

a

more

sophisticated

parameterization

of

the physical

circulation.

Also, the particle-in-cell model

can be modified to

explicitly include chemical reactions and

interactions

with the biota. A model should be used

in

the

context

of the

level of resolution

or

aggregation

that

is

known

about

the ecosystem and

the

management

decision to

the

made.

Models are

used

also

as

an

aid in

selecting

situations

that

merit further analysis

with more

comprehensive

ecologi-

cal

reasoning.

100



Reviewer's

Comments

This

model is

based on

a

numerical

hydrodynamic

model of the area under

study.

One of

the difficulties

in

applying

models

of

this type

to

other regions

is

the

determination

of

the model

boundaries

and treatment

of

the

boundary

cells

(free, fixed, no-slip,

reflecting),

A

disadvantage

in

the use of models of this type is

the

required

cost

of

computation

—

even on

the

largest,

most

sophisticated computers.

101



Model Name

or

Description

Reference

The

U.S.

Geological

Survey

Oil

Spill

Trajectory

Analysis

(OSTA)

Model

Samuels,

W.B.,

The

USGS

Oil

Spill

Trajectory

Analysis

Model,

Proceedings

of

the

Workshop

on

Government

Oil

Spill

Modeling

,

November 7-9,

1979,

Wallops

Island,

Virginia,

NOAA,

Washington,

D.

C,

February

1980.

Abstract

The

USGS oil spill trajectory

analysis

model

(OSTA) is used

to

calculate the

probability

of oil

spills

occurring

and contacting

environmental

resources and sections

of

the

coastline.

A grid

system

is superimposed

on the

study area

with

a

maximum

of

480

miles

on

a

side.

The

dimension

of

the

grid

cell

is

variable

depending

on the

size

of

the

study

area.

Locations

of

environmental

resources

proposed

and existing

lease tracts, and oil

transportation

routes (pipeline

and

tanker) are

determined

by

their

positions

in

the

model's grid system.

Data from

different

map

projections

can

be

digitized

and

fitted

into

the

model's

grid

system

by

coordinate

conversion

subroutines. A maximum

of 31 categories

of

resources and

up

to

100

segments

(2

different

sets)

of

the coastline can be

included in the

analysis.

Oil

spills are

simulated

in

a

Monte

Carlo

fashion.

Typically, 500

simulated

oil

spills

are

launched per season

from

each launch point

(platform

location,

pipeline,

or

tanker

route).

Spills

are transported by

monthly

currents

and

by winds sampled from

wind

transition

matrices. These

matrices,

composed

of 41

wind

velocity

states,

are

based

on

historic

wind

records.

They are

constructed

for

each

season for up to

six wind stations. Surface ocean

currents

are

incorporated

in

a

deterministic manner by

representing

monthly

current fields

in

the

model's grid

system.

The

spill

movement algorithm

consists

of

computing

the

vector

sum

of

a

wind

and

current vector for

successive

3-hour

increments. Each grid cell

in

the path of

the

spill

is

checked for

the presence

or

absence

of

each

environmental

resource. Spill movement ends in one

of

three ways:

1)

the spill

contacts

land,

2)

the

spill

decays

at

sea,

or

3)

the spill moves

off

the

map.

102



Conditional

probabilities

of

contact

are reported

for

3-,

]

0-

,

and

30-

day travel times. Oil spill occurrence

is treated

as a

Poisson

process, in which

the

exposure

variable is the

volume of oil produced

or

transported.

Scenarios

outlining

proposed

oil

production and transportation

are

constructed

for various alternatives.

The

overall risks

are

determined

by

combining

spill

occurrence probabilities.

Recent applications

of the model have been:

Sale

55 (Northern

Gulf

of

Alaska, Sale 53

(Northern and

Central California),

and

Sale 46 (Kodiak Island).

Reviewer's

Comment s

This

model uses

a vectorial

approach of

wind and

current

to

simulate advection.

The

use

of input

data

is

very

similar

to the DPPO model.

The

movement of

the slick

is

tracked for

a specified duration of

time via

employment

of actual

data

or of

simulated

data

(based on

a

Markov

chain

model)

if

real

data

is

not

available.

This

model

has been

used for

environmental

assessment

in

connection

with

a

number

of

offshore

lease

sales (e.g.,

Alaska, Gulf

of

Mexico,

Southern

California and North-,

Mid-

and South

Atlantic).

103



Model

Name

or Description

On-Scene

Spill

Model

(OSSM)

Pacific

Marine

Environmental

Laboratory

NOAA, Seattle,

Washington

Reference

(a) Torgrimson,

G.M., and

J. A.

Gait,

An On-Scene

Spill

Model

for

Pollutant

Trajectory Simulation,

Workshop on the

Physical

Behavior

of

Oil in

the

Marine

Environment

,

Princeton

University,

Princeton, New

Jersey

(b) Gait,

J.A.

,

and G.M. Torgrimson ,

On-Scene

Trajectory Modelling for the U.S. Response

to

the

IXTOC-1 Blowout, Proceedings

of

the

Workshop on

Government

Oil

Spill Modeling

,

November

7-9,

1979,

Wallops

Island,

Virginia,

NOAA,

Washington,

D.C.,

February

1980.

Abstract

(a)

The

Pacific Marine

Environmental

Laboratory's

Hazardous Materials

Scientific Support Team

(PMEL/HMSST)

has developed

a data

management system for

the

rapid

simulation

of

pollutant trajectories in the

marine

environment. The On Scene Spill

Model

(OSSM) has been

designed

to function

at

several

different

levels of

complexity depending

on

user

requirements

and

available

environmental

data. OSSM may

be

utilized as

an

environ-

mental

assessment

tool

to

predict pollutant

trajectories

and coastal impact areas, given hypothetical

pollutant

spills.

General cautions

about interpreting

the

output

are included.

Planned

modifications and

additions to

the

existing

program

are

listed.

The

data

management

system was used

to

document

and

predict pollutant

trajectories

during the

PECK SLIP oil

spill off the

east coast

of Puerto

Rico

on December

19,

1978.

(b)

During

the

spill event

associated

with the

IXTOC

I

well blowout,

the

U.S.

National Contingency

Plan was

activated. In anticipation of

this,

the NOAA

Hazardous

Materials

Response

Project

requested

the

Hazardous Materials

Scientific

Support

Team

(for

physical

processes)

to

supply trajectory

information

through

the

scientific support

coordinator.

This

was done

beginning

June

12,

1979.

During the

summer,

this

plan

required

a

variety

of

activities including:

(1)

collecting

available

104



background information,

(2)

carrying

out

observational

field programs,

(3)

coordinating data

and

information

presented

by

other

researchers (Federal,

State and private)

and

(4)

analyzing

trajectories.

During

the

spill,

trajectory

models

were

used

in

basically

three

different forms.

The first

was

in

a

long-term statistically

controlled form

(strategic) for

planning

call

up and

retirement

of

scientific

or

cleanup

units.

The second was

a

short-term

localized

forecast

(tactical)

for input

into

day-to-day

planning.

The third

was

in

a receptor

mode that identified

danger zones

that

could

impact

scientific

high-valued

regions.

This, in

turn, was used

to

develop optimal mapping

strategies for

overflights

The

basic model

for

IXTOC

I

studies

was

a

new

version

of

OSSM

(On-Scene

Spill Model)

incorporating

a

number of

advanced

features. In addition,

several

auxiliary

programs to

analyze

circulation data

were also

used for

the first time in

a

real

spill

situation.

Both

hindcasts

and forecasts

from

the

models

have

provided

useful

input

to the

overall response program..

Reviewer's Comments

This

model

is undergoing

continuing

development

and

improvement.

The

model

is

designed to

be

utilized

as a

real-time

spill

trajectory model,

Advection

is

handled

in

vector fashion

from

both

wind and current.

Diffusion

is

currently

modeled

via

a

Monte

Carlo approach

to

the

governing

diffusion

equations.

Other

algorithms

are

being

considered which

would more accurately

simulate spread-

ing

and

diffusion.

Additional

details

will

be

provided in

the

1981

Joint Conference

on

Prevention and

Control of

Oil

Spills

which will

be

available

in

September,

1982.

105



Model

Name or

Description

DRIFT

Reference

Hunter,

J.R.,

An

Interactive Computer

Model

of Oil

Slick

Motion,

Oceanology

International

'80,

Abstract

(from

text)

An

interactive

computer

model has

been

developed

to

predict

the

motion

of

an

oil slick

on

the

sea

surface

which is

particularly

suited

to

the shallow waters

of

the

sea shelf.

Wind-induced drift

and

spreading

are

considered

to be the most

important mechanisms

in

this

motion. The

wind-induced

drift is modeled

via an empirical relationship

and the

spreading,

mixing

and

decay are

modeled

using

Monte

Carlo

techniques.

The

model

has been

applied

to

an

area

of Irish

sea

near

Anglesey,

U.K.,

and has predicted

at

least

one

recent

spill

successfully.

Reviewer's Comments

This

model

is

a

classical

deterministic

approach

which incorporates

the

major

mechanisms

of

importance

to

the

prediction

of

the

motion

of an

oil

spill

in

the

area

for

which

it was designed. One of the underlying assumptions

in this model is that spreading

is

caused

by

turbulence

and lateral velocity

shears.

As

a

consequence,

this

model

should not

be

used

to predict

oil spill behavior during

early stages

following

the

initial

spill.

The justification

for the approach

that

has

been employed

is

based

on

a

few

observations

of

very

large spills wherein it was noted

that

spill

diameter

increases

with the

first power

of

time.

With

proper

imput

,

the model appears

to

provide

106



reasonable predictions.

However,

for

predictions

nearshore

the

model is

very

sensitive to

errors in certain

input

information. Therefore,

use

of

the

model

in

an operational

mode

requires

continuous updating

of

input

information.

107



LIBRARY

OF NORTH

CAROLINA

3 3091

00748

0361

CEIP Publications

1.

Hauser, E.

W.

,

P.

D.

Cribbins, P.

D.

Tschetter, and

R.

D.

Latta.

Coastal

Energy

Transportation

Needs to Support

Major Energy Projects

in

North Carolina's

Coastal Zone. CEIP

Report

iH.

September

1981.

$10.

2.

P. D. Cribbins. A

Study

of

OCS

Onshore

Support

Bases and Coal

Export

Terminals.

CEIP Report

#2.

September

1981.

$10.

3.

Tschetter, P. D.,

M.

Fisch,

and R.

D. Latta.

An Assessment of

Potential

Impacts

of

Energy-Related

Transportation Developments on

North

Carolina's

Coastal

Zone.

CEIP Report

#3.

July

1981.

$10.

4.

Cribbins,

P.

S.

An Analysis

of

State and Federal Policies

Affecting

Major Energy

Projects

in

North Carolina's Coastal Zone. CEIP

Report

#4.

September

1981.

$10.

5.

Brower, David,

W.

D.

McElyea, D.

R.

Godschalk, and N.

D.

Lofaro.

Outer Continental Shelf Development and the North Carolina Coast:

A

Guide

for

Local Planners. CEIP Report

#5.

August

1981.

$10.

6.

Rogers, Golden

and

Halpern,

Inc., and

Engineers

for

Energy

and

the

Environment,

Inc. Mitigating the Impacts of Energy

Facilities:

A

Local Air Quality Program for

the Wilmington,

N.

C.

Area.

CEIP

Report

#6.

September

1981.

$10.

7.

Richardson,

C.

J. (editor).

Pocosin Wetlands:

an

Integrated

Analysis

of

Coastal Plain Freshwater Bogs

in

North Carolina. Stroudsburg

(Pa):

Hutchinson Ross.

364

pp.

$25.

Available

from

School of Forestry,

Duke University, Durham, N.

C.

27709.

(This proceedings

volume

is

for

a

conference

partially

funded

by

N.

C.

CEIP.

It

replaces

the

N.

C.

Peat

Sourcebook

in

this publication list.)

8.

McDonald,

C. B. and

A. M.

Ash. Natural

Areas

Inventory of

Tyrrell

County,

N.

C.

CEIP

Report

#8.

October

1981.

$10.

9.

Fussell, J.,

and

E.

J. Wilson.

Natural

Areas

Inventory

of

Carteret

County, N.

C.

CEIP

Report

#9.

October

1981.

$10.

10.

Nyfong,

T. D,

Natural

Areas Inventory

of Brunswick

County, N.

C.

CEIP

Report

#10.

October

1981.

$10.

11.

Leonard,

S.

W.,

and

R.

J.

Davis.

Natural Areas Inventory

for

Pender

County,

N. C.

CEIP

Report

#11.

October

1981.

$10.

12. Cribbins,

Paul

D.,

and

Latta,

R. Daniel.

Coastal

Energy

Transporta-

tion Study:

Alternative

Technologies for

Transporting

and

Handling

Export

Coal. CEIP Report #12.

January

1982.

$10.

13.

Creveling, Kenneth. Beach Communities

and

Oil

Spills:

Environmental

and

Economic

Consequences

for Brunswick

County,

N.

C.

CEIP Report

#13.

May 1982.

$10.



CEIP Publications

14.

Rogers,

Golden and

Halpern, Inc.,

and

Engineers

for

Energy

and

the

Environment.

The

Design

of a

Planning Program to

Help

Mitigate Energy

Facility-Related

Air

Quality Impacts in

the

Washington County,

North

Carolina

Area. CEIP

Report

#14.

September

1982.

$10.

15.

Fussell,

J.,

C.

B.

McDonald,

and

A.

M.

Ash.

Natural

Areas

Inventory

of Craven

County,

North

Carolina.

CEIP

Report

#15.

October 1982.

$10.

16.

Frost, Cecil C.

Natural

Areas

Inventory of

Gates County, North

Carolina.

CEIP Report

#16.

April

1982.

$10.

17.

Stone, John R.,

Michael T.

Stanley,

and Paul T. Tschetter. Coastal

Energy

Transportation

Study, Phase III,

Volume

3:

Impacts

of

Increased

Rail Traffic

on

Communities in Eastern

North

Carolina.

CEIP Report

#17.

August 1982.

$10.

19.

Pate, Preston P., and

Jones,

Robert.

Effects of

Upland

Drainage on

Estuarine

Nursery Areas of Pamlico

Sound,

North

Carolina. CEIP

Report

#19.

December

1981.

$1.00.

25. Wang Engineering

Co.,

Inc.

Analysis

of

the

Impact

of Coal Trains

Moving

Through Morehead

City, North Carolina. CEIP

Report

#25.

October 1982.

$10.

26.

Anderson

&

Associates,

Inc.

Coal Train

Movements

Through

the

City

of

Wilmington,

North Carolina. CEIP

Report

#26.

October 1982.

$10.

27.

Peacock,

S.

Lance and

J.

Merrill

Lynch.


of

Mainland Dare County,

North

Carolina.

CEIP

Report

#27.

November

1982.

$10.

28. Lynch,

J.

Merrill

and S. Lance

Peacock.

Natural

Areas

Inventory

of

Hyde

County,

North

Carolina.

CEIP Report

#28.

October

1982.

$10.

29.

Peacock,

S.

Lance

and

J. Merrill

Lynch.


of

Pamlico

County, North Carolina. CEIP

Report

#29.

November

1982.

$10.

30.

Lynch,

J. Merrill and

S,

Lance

Peacock.


of

Washington

County, North Carolina. CEIP

Report

#30.

October

1982.

$10.

31. Muga,

Bruce

J.

Review

and

Evaluation of

Oil Spill

Models

for Applica-

tion

to

North

Carolina Waters.

CEIP Report

#31.

August 1982.

$10.

33.

Sorrell,

F. Yates and

Richard

R.

Johnson. Oil

and

Gas Pipelines

in

Coastal North

Carolina: Impacts and Routing Considerations.

CEIP

Report

#33.

December

1982.

$10.

34.

Roberts

and Eichler

Associates,

Inc. Area Development Plan

for

Radio

Island. CEIP Report

#34.

June

1983.

$10.

35.

Cribbins,

Paul

D.

Coastal Energy

Transportation

Study, Phase

III,

Volume

4:

The

Potential

for

Wide-Beam, Shallow-Draft

Ships

to

Serve

Coal

and

Other

Bulk Commodity

Terminals along

the

Cape

Fear

River.

CEIP

Report

#35.

August

1982.

$10.

h Oil Spill Archive

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